In this paper, the design of decentralized switching control for uncertain multivariable plants is considered. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model and specific control structure. The underlying design is based on the quantitative feedback theory (QFT). It is assumed that a MIMO-QFT controller exists for robust stability and performance of the individual uncertain sets. The proposed control structure is made up by these local decentralized controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the local models’ behaviors with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down the switching to guarantee the overall closed loop stability. It is shown that this strategy provides a stable and robust adaptive controller to deal with complex multivariable plants with input–output pairing changes during the plant operation, which can facilitate the development of a reconfigurable decentralized control. Also, the multirealization technique is used to implement a family of controllers to achieve bumpless transfer. Simulation results are employed to show the effectiveness of the proposed method.
On an LAS-integrated soft PLC system based on WorldFIP fieldbusISA Interchange
Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable.
Tracy–Widom distribution based fault detection approach: Application to aircr...ISA Interchange
The fault detection approach based on the Tracy–Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy–Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined.
A portable hardware in-the-loop device for automotive diagnostic control systemsISA Interchange
In-vehicle driving tests for evaluating the performance and diagnostic functionalities of engine control systems are often time consuming, expensive, and not reproducible. Using a hardware-in-the-loop (HIL) simulation approach, new control strategies and diagnostic functions on a controller area network (CAN) line can be easily tested in real time, in order to reduce the effort and the cost of the testing phase. Nowadays, spark ignition engines are controlled by an electronic control unit (ECU) with a large number of embedded sensors and actuators. In order to meet the rising demand of lower emissions and fuel consumption, an increasing number of control functions are added into such a unit. This work aims at presenting a portable electronic environment system, suited for HIL simulations, in order to test the engine control software and the diagnostic functionality on a CAN line, respectively, through non-regression and diagnostic tests. The performances of the proposed electronic device, called a micro hardware-in-the-loop system, are presented through the testing of the engine management system software of a 1.6 l Fiat gasoline engine with variable valve actuation for the ECU development version.
PI and fuzzy logic controllers for shunt active power filterISA Interchange
This paper presents a shunt Active Power Filter (APF) for power quality improvements in terms of harmonics and reactive power compensation in the distribution network. The compensation process is based only on source current extraction that reduces the number of sensors as well as its complexity. A Proportional Integral (PI) or Fuzzy Logic Controller (FLC) is used to extract the required reference current from the distorted line-current, and this controls the DC-side capacitor voltage of the inverter. The shunt APF is implemented with PWM-current controlled Voltage Source Inverter (VSI) and the switching patterns are generated through a novel Adaptive-Fuzzy Hysteresis Current Controller (A-F-HCC). The proposed adaptive-fuzzy-HCC is compared with fixed-HCC and adaptive-HCC techniques and the superior features of this novel approach are established. The FLC based shunt APF system is validated through extensive simulation for diode-rectifier/R–L loads.
IRJET- Excitation Control of Synchronous Generator using a Fuzzy Logic based ...IRJET Journal
This document presents a fuzzy logic-based backstepping approach for excitation control of synchronous generators. The backstepping control law is designed using control Lyapunov functions to ensure stability. Fuzzy logic is then used to determine the optimal values for three tuning gains in the backstepping control law. Membership functions are defined based on the CLF boundaries. Fuzzy rules are formulated to map error and change in error inputs to tuning gain outputs. Simulation studies on a single machine infinite bus system evaluate the performance of the proposed controller under two fault conditions, and validate that it improves stability compared to traditional controllers with constant gains.
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for
Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to
hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware
implementation due to low consumption of energy, high speed of operation and large capacity of data storage.
In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the
implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description
Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop
FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller
algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board.
IRJET- Analysis of 3-Phase Induction Motor with High Step-Up PWM DC-DC Conver...IRJET Journal
This document discusses control methods for STATCOMs using fuzzy logic controllers and genetic algorithm-tuned PID controllers. STATCOMs are shunt FACTS devices that help solve power quality issues through fast reactive power control. Conventionally, PID controllers are used but require trial and error to tune parameters. The document proposes using fuzzy logic controllers and genetic algorithms to optimize PID parameters to improve STATCOM current control response. It describes STATCOM modeling, fuzzy logic controller design including fuzzification, inference, and defuzzification. Genetic algorithms are used to find optimal PID parameters. Simulation results in MATLAB show the proposed methods improve current control response over conventional PID control.
On an LAS-integrated soft PLC system based on WorldFIP fieldbusISA Interchange
Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable.
Tracy–Widom distribution based fault detection approach: Application to aircr...ISA Interchange
The fault detection approach based on the Tracy–Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy–Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined.
A portable hardware in-the-loop device for automotive diagnostic control systemsISA Interchange
In-vehicle driving tests for evaluating the performance and diagnostic functionalities of engine control systems are often time consuming, expensive, and not reproducible. Using a hardware-in-the-loop (HIL) simulation approach, new control strategies and diagnostic functions on a controller area network (CAN) line can be easily tested in real time, in order to reduce the effort and the cost of the testing phase. Nowadays, spark ignition engines are controlled by an electronic control unit (ECU) with a large number of embedded sensors and actuators. In order to meet the rising demand of lower emissions and fuel consumption, an increasing number of control functions are added into such a unit. This work aims at presenting a portable electronic environment system, suited for HIL simulations, in order to test the engine control software and the diagnostic functionality on a CAN line, respectively, through non-regression and diagnostic tests. The performances of the proposed electronic device, called a micro hardware-in-the-loop system, are presented through the testing of the engine management system software of a 1.6 l Fiat gasoline engine with variable valve actuation for the ECU development version.
PI and fuzzy logic controllers for shunt active power filterISA Interchange
This paper presents a shunt Active Power Filter (APF) for power quality improvements in terms of harmonics and reactive power compensation in the distribution network. The compensation process is based only on source current extraction that reduces the number of sensors as well as its complexity. A Proportional Integral (PI) or Fuzzy Logic Controller (FLC) is used to extract the required reference current from the distorted line-current, and this controls the DC-side capacitor voltage of the inverter. The shunt APF is implemented with PWM-current controlled Voltage Source Inverter (VSI) and the switching patterns are generated through a novel Adaptive-Fuzzy Hysteresis Current Controller (A-F-HCC). The proposed adaptive-fuzzy-HCC is compared with fixed-HCC and adaptive-HCC techniques and the superior features of this novel approach are established. The FLC based shunt APF system is validated through extensive simulation for diode-rectifier/R–L loads.
IRJET- Excitation Control of Synchronous Generator using a Fuzzy Logic based ...IRJET Journal
This document presents a fuzzy logic-based backstepping approach for excitation control of synchronous generators. The backstepping control law is designed using control Lyapunov functions to ensure stability. Fuzzy logic is then used to determine the optimal values for three tuning gains in the backstepping control law. Membership functions are defined based on the CLF boundaries. Fuzzy rules are formulated to map error and change in error inputs to tuning gain outputs. Simulation studies on a single machine infinite bus system evaluate the performance of the proposed controller under two fault conditions, and validate that it improves stability compared to traditional controllers with constant gains.
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for
Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to
hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware
implementation due to low consumption of energy, high speed of operation and large capacity of data storage.
In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the
implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description
Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop
FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller
algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board.
IRJET- Analysis of 3-Phase Induction Motor with High Step-Up PWM DC-DC Conver...IRJET Journal
This document discusses control methods for STATCOMs using fuzzy logic controllers and genetic algorithm-tuned PID controllers. STATCOMs are shunt FACTS devices that help solve power quality issues through fast reactive power control. Conventionally, PID controllers are used but require trial and error to tune parameters. The document proposes using fuzzy logic controllers and genetic algorithms to optimize PID parameters to improve STATCOM current control response. It describes STATCOM modeling, fuzzy logic controller design including fuzzification, inference, and defuzzification. Genetic algorithms are used to find optimal PID parameters. Simulation results in MATLAB show the proposed methods improve current control response over conventional PID control.
1) The document presents a study on implementing a fuzzy logic controller for an AC generator to improve transient stability.
2) A single machine infinite bus power system model is used to evaluate the fuzzy logic controller and compare it to a conventional power system stabilizer.
3) The fuzzy logic controller uses the speed deviation and acceleration of the generator rotor as inputs, and computes stabilizing signals based on these variables and fuzzy membership functions to dampen mechanical oscillations.
DC Motor Position Control Using Fuzzy Proportional-Derivative Controllers Wit...IOSR Journals
This document discusses controlling the position of a DC motor using fuzzy proportional-derivative controllers with different defuzzification methods. It first introduces Shravan Kumar Yadav and his background. It then models a DC motor in Simulink and designs a crisp PD controller as a benchmark. Different fuzzy PD controllers using various defuzzification methods are implemented and their responses compared. The fuzzy controllers are able to reject disturbances without retuning, unlike the crisp PD controller. The purpose is to control DC motor position using fuzzy logic control in MATLAB and compare its performance to PID control.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
This document presents a comparison of PID and fuzzy PID controllers for position control of a DC motor. It first describes the modeling of a DC motor transfer function. It then provides details on designing a PID controller using Ziegler-Nichols tuning methods. A fuzzy PID controller is also designed using triangular membership functions for error and change in error inputs. Simulation results in MATLAB/Simulink show that the fuzzy PID controller provides better tracking of setpoint changes with less overshoot compared to the ZN-tuned PID controller. The fuzzy PID controller therefore demonstrates better performance for position control of DC motors.
Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model app...IJECEIAES
This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of egyptian load frequency control (ELFC). In this technique, the inputs to a TS fuzzy model are the parameters of the change of operating points. The TS fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDCPID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed optimal PID controller.
DEVELOPMENT OF FUZZY LOGIC LQR CONTROL INTEGRATION FOR AERIAL REFUELING AUTOP...Ahmed Momtaz Hosny, PhD
This document summarizes research on integrating fuzzy logic control with linear quadratic regulator (LQR) control for an aerial refueling autopilot. It describes modeling an aircraft, applying LQR control alone and with fuzzy logic control integrated. The integrated LQR fuzzy control is shown to more effectively suppress uncertainties and minimize mission time compared to LQR alone. Key aspects covered include aircraft modeling, optimal LQR flight control, applying fuzzy inference systems, deriving fuzzy rules, and the integrated LQR fuzzy control structure applied to pitch and lateral control for aerial refueling simulations.
To design and implementation of variable and constant with no load for induction motor (IM) that is the goal in this work. This paper was including three parts, first the simulation model with no load for IM, Second the simulation model with constant load for IM, Third the simulation model with variable load for IM. In addition, this work includes comparative between two different controllers (PI and fuzzy logic control (FLC). The simulation results clearly the implementation of variable and constant with no load for IM. The simulation response of the system achieves better results when choosing to use type fuzzy-PI controller technique comparison with conventional PI controller and improve the performance of the system at different operation conditions.
Adaptive PI Controller for Voltage Regulation in Power SystemsISA Interchange
Static synchronous compensator (STATCOM) provides the means to improve quality and reliability of a power system as it has the functional capability to handle dynamic disturbances, such as transient stability and power oscillation damping as well as to providing voltage regulation. In this paper, a robust adaptive PI-based optimal fuzzy control strategy is proposed to control a STATCOM used in distribution systems. The proposed intelligent strategy is based on a combination of a new General Type-II Fuzzy Logic (GT2FL) with a simple heuristic algorithm named Teaching Learning Based Optimization (TLBO) Algorithm. The proposed framework optimally tunes parameters of a Proportional-Integral (PI) controller which, similar to most of other researchers regarding control of STATCOM, are in charge of controlling the device. The proposed controller guaranties robustness and stability against uncertainties caused by external disturbances or ever-changing nature of the power systems. The TLBO optimizes the parameters of the controller as well as the input and output membership functions. To validate the efficiency of the proposed controller, the obtained simulation results are compared with those of the two most recent researches applied in this field, namely, conventional Proportional Integral (PI) controller and Optimal Fuzzy PI (OFPI) controller. Results demonstrate the successfulness and effectiveness of the proposed online-TLBO General Type-2 Fuzzy PI (OGT2FPI) controller and its superiority over conventional approaches.
IRJET- Optimum Design of PSO based Tuning using PID Controller for an Automat...IRJET Journal
This document discusses using particle swarm optimization (PSO) to tune the parameters of a PID controller for an automatic voltage regulator (AVR) system. The goal is to improve the system's transient performance by minimizing overshoot and steady state error. PSO is applied to optimize the proportional, integral, and derivative parameters of the PID controller. Simulation results show the PSO-tuned PID controller provides significantly better control of the AVR system compared to a traditionally tuned PID controller. The tuned controller gives faster response, lower overshoot, and improved stability when subjected to disturbances and parameter variations.
This document describes a PID controller with self-tuning capabilities using fuzzy logic. It replaces the conventional PID controller in a chopper-fed DC motor drive system to improve performance. The PID gains (KP, KI, KD) are automatically tuned online by a fuzzy logic controller based on the error and change in error. This allows the PID gains to adapt as needed for different operating conditions. Simulation results showed the proposed self-tuning PID controller performed better than a conventional PID controller.
Design Novel Nonlinear Controller Applied to Robot Manipulator: Design New Fe...Waqas Tariq
This document describes a novel adaptive feedback linearization fuzzy controller for robot manipulators. It begins by discussing limitations of traditional feedback linearization controllers, such as sensitivity to parameter uncertainty. It then proposes designing a feedback linearization fuzzy controller to address this issue. The key steps are: 1) designing the fuzzy controller, including fuzzifying inputs/outputs and developing a rule base, 2) developing an adaptive feedback linearization fuzzy controller by adding an adaptive law to tune fuzzy rule parameters online and improve disturbance rejection. The goal is to develop a robust position controller for robot manipulators that maintains acceptable performance despite nonlinearities and uncertainty.
This paper introduces experimental comparison study between six and four switch inverter fed three phase induction motor drive system. The control strategy of the drive is based on speed sensoreless vector control using model reference adaptive system as a speed estimator. The adaptive mechanism of speed control loop depends on fuzzy logic control. Four switch inverter conFigureurations reduces the cost of the inverter, the switching losses, the complexity of the control algorithms, interface circuits, the computation of real-time implementation, volume-compactness and reliability of the drive system. The robustness of the proposed model reference adaptive system based on four switch three-phase inverter (FSTPI) fed induction motor drive is verified experimentally at different operating conditions. Experimental work is carried using digital signal processor (DSP1103) for a 1.1 kW motor. A performance comparison of the proposed FSTP inverter fed IM drive with a conventional six switch three-phase inverter (SSTP) inverter system is also made in terms of speed response. The results show that the proposed drive system provides a fast speed response and good disturbance rejection capability. The proposed FSTP inverter fed IM drive is found quite acceptable considering its performance, cost reduction and other advantages features.
The aim of this paper is to prove that fuzzy logic algorithm is a suitable control technique for fast processes such as electrical machines. This theory has been experimented on different kinds of electrical machines such as stepping motors, dc motors and induction machines (with 6 phases) and the experimental results show that the proposed fuzzy logic algorithm is the most suitable control technique for electrical machines since this algorithm is not time consuming and it is also robust between plant parameters variations.
IRJET- Speed Control of Induction Motor using Hybrid PID Fuzzy ControllerIRJET Journal
This document presents a study on using a hybrid PID fuzzy controller with a BAT optimization algorithm to control the speed of an induction motor. It begins with background on PID controllers and fuzzy logic controllers. It then proposes using a BAT algorithm to select the Kp and Ki parameters of a PI controller to regulate motor speed. The results show that the proposed BAT-PID controller reduces speed fluctuations and settling time compared to a traditional PID controller. In conclusion, the hybrid fuzzy-PID controller with BAT optimization improves induction motor speed control.
Direct digital control scheme for controlling hybrid dynamic systems using AN...XiaoLaui
An Estimator Based Inverse Dynamics Controller (EBIDC), which utilizes an Artificial Neural Network (ANN) based state estimation scheme for nonlinear autonomous hybrid systems which are subjected to state disturbances and measurement noises that are stochastic in nature, is proposed in this paper. A salient feature of the proposed scheme is that it offers better state estimates and hence a better control of non-measurable state variables with a non linear approach in correcting the a priori estimates by avoiding statistical linearization involved in existing approaches based on derivative free estimation methods. Simulation results guarantees significant reduction in Integral Square Error (ISE) and standard deviation (σ) of error, between the controlled variable and set point and control signal computation time when compared with best existing related work based on Unscented Kalman Filter (UKF) and Ensembeled Kalman Filter (EnKF). Detailed analysis of the experimental results on real plant under different operating conditions such as servo and regulatory operations, initial condition mismatch, and different types of faults in the system, confirms robustness of proposed approach in these conditions and support the simulation results obtained. The main advantage of the proposed controller is that the control signal computation time is very much less than the selected sampling time of the process, so direct control of the plant is possible with this approach.
Clock Gating of Streaming Applications for Power Minimization on FPGA’sIRJET Journal
This document discusses using clock gating techniques to reduce power consumption in streaming applications implemented on FPGAs. It introduces a method to selectively disable clock signals to inactive parts of a circuit to minimize dynamic power. The technique can be automatically applied during synthesis of dataflow designs for streaming applications. Experimental results on an MPEG-4 video decoder demonstrated power reductions of up to 30% with no loss in throughput.
Implementation of closed loop control technique for improving the performance...IJERA Editor
this review paper presents closed loop control techniques for controlling the inverter working under different load or KVA ratings. The control strategy of the inverter must guarantee its output waveforms to be sinusoidal with fundamental harmonic. For this purpose, close loop current control strategies such as H∞ repetitive controller, dual closed-loop feedback control, Adaptive Voltage Control, SRFPI controller, Optimal Neural Controller, etc. have been used to meet the power quality requirements imposed by IEEE Interconnection Standards. Based on present scenario regarding energy crises, immediate action is the use of different renewable energy sources (RESs) . Out of RESs, solar is gaining more attention. It is very important to design and developed a system which should be efficient enough to utilize the extracted energy for different types of load and feeding of energy into utility grid. Since experimentation and comparison of such inverter models on hardware being relatively expensive, the latest computing tool like MATLAB are considered to be a better alternative to simulate the outcomes of such expensive systems. The proposed closed loop control technique for the inverter working under linear and nonlinear system will be implemented in MATLAB/SIMULINK working platform and results will be analyzed to check its benefits.
IRJET- Load Frequency Control of a Wind Integrated Power System using Convent...IRJET Journal
This document summarizes a research paper that proposes using a fuzzy proportional-integral-derivative (FPID) controller for load frequency control of a power system integrated with wind power. The system being studied is a four-area power system with each area containing wind, hydro, and thermal power plants. Simulation results show that the system with renewable energy sources gives better dynamic response when using an FPID controller compared to using a conventional PID controller. The FPID controller is able to better suppress frequency deviations caused by load and power fluctuations from the renewable energy sources.
Shale Gas Opportunities for ISA in North AmericaISA Interchange
This document discusses potential opportunities for the Instrumentation, Systems, and Automation Society (ISA) to become involved in the shale gas industry in North America. It proposes a 9-step process for ISA to explore one such opportunity around workforce development and education/training. The steps include developing an ISA value proposition customized for shale gas, assessing market opportunities in 3 shale basins, meeting with key regional stakeholders, and determining a champion within ISA to pursue an initial deal. The overall aim is to leverage ISA's expertise in educational standards and training to help accelerate workforce development for the shale gas industry through partnerships with regional organizations, oil and gas companies, and community colleges.
Simulation and stability analysis of neural network based control scheme for ...ISA Interchange
This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709–14] is presented.
Sufficient condition for stabilization of linear time invariant fractional or...ISA Interchange
This paper presents the stabilization problem of a linear time invariant fractional order (LTI-FO) switched system with order 1<q><21><q><2><q><21><q><2 based on the convex analysis and linear matrix inequality (LMI) is presented and proved. Then a single Lyapunov function, whose derivative is negative, is constructed based on the extremum seeking method. A sliding sector is designed for each subsystem of the LTI-FO switched system so that each state in the state space is inside at least one sliding sector with its corresponding subsystem, where the Lyapunov function found by the extremum seeking control is decreasing. Finally, a switching control law is designed to switch the LTI-FO switched system among subsystems to ensure the decrease of the Lyapunov function in the state space. Simulation results are given to show the effectiveness of the proposed VS controller.
Eliminating Difficult Start-ups with State Based ControlsISA Interchange
The document discusses challenges with starting up difficult processes and how total automation can help address these challenges. It notes that issues like operator error, aging workforces, variability in operator skills, and process complexity can prolong startups and cause errors. Total automation, where the entire startup process is automated using advanced control strategies, regulatory controls, and state logic, can reduce startup times by half to two-thirds and make the process more reliable and repeatable. It also discusses elements that make processes difficult to control, like small operating envelopes and multitasking requirements, and how automation can help maintain critical process boundaries.
Identification and real time position control of a servo-hydraulic rotary act...ISA Interchange
This paper presents a new intelligent approach for adaptive control of a nonlinear dynamic system. A modified version of the brain emotional learning based intelligent controller (BELBIC), a bio-inspired algorithm based upon a computational model of emotional learning which occurs in the amygdala, is utilized for position controlling a real laboratorial rotary electro-hydraulic servo (EHS) system. EHS systems are known to be nonlinear and non-smooth due to many factors such as leakage, friction, hysteresis, null shift, saturation, dead zone, and especially fluid flow expression through the servo valve. The large value of these factors can easily influence the control performance in the presence of a poor design. In this paper, a mathematical model of the EHS system is derived, and then the parameters of the model are identified using the recursive least squares method. In the next step, a BELBIC is designed based on this dynamic model and utilized to control the real laboratorial EHS system. To prove the effectiveness of the modified BELBIC’s online learning ability in reducing the overall tracking error, results have been compared to those obtained from an optimal PID controller, an auto-tuned fuzzy PI controller (ATFPIC), and a neural network predictive controller (NNPC) under similar circumstances. The results demonstrate not only excellent improvement in control action, but also less energy consumption.
1) The document presents a study on implementing a fuzzy logic controller for an AC generator to improve transient stability.
2) A single machine infinite bus power system model is used to evaluate the fuzzy logic controller and compare it to a conventional power system stabilizer.
3) The fuzzy logic controller uses the speed deviation and acceleration of the generator rotor as inputs, and computes stabilizing signals based on these variables and fuzzy membership functions to dampen mechanical oscillations.
DC Motor Position Control Using Fuzzy Proportional-Derivative Controllers Wit...IOSR Journals
This document discusses controlling the position of a DC motor using fuzzy proportional-derivative controllers with different defuzzification methods. It first introduces Shravan Kumar Yadav and his background. It then models a DC motor in Simulink and designs a crisp PD controller as a benchmark. Different fuzzy PD controllers using various defuzzification methods are implemented and their responses compared. The fuzzy controllers are able to reject disturbances without retuning, unlike the crisp PD controller. The purpose is to control DC motor position using fuzzy logic control in MATLAB and compare its performance to PID control.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
This document presents a comparison of PID and fuzzy PID controllers for position control of a DC motor. It first describes the modeling of a DC motor transfer function. It then provides details on designing a PID controller using Ziegler-Nichols tuning methods. A fuzzy PID controller is also designed using triangular membership functions for error and change in error inputs. Simulation results in MATLAB/Simulink show that the fuzzy PID controller provides better tracking of setpoint changes with less overshoot compared to the ZN-tuned PID controller. The fuzzy PID controller therefore demonstrates better performance for position control of DC motors.
Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model app...IJECEIAES
This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of egyptian load frequency control (ELFC). In this technique, the inputs to a TS fuzzy model are the parameters of the change of operating points. The TS fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDCPID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed optimal PID controller.
DEVELOPMENT OF FUZZY LOGIC LQR CONTROL INTEGRATION FOR AERIAL REFUELING AUTOP...Ahmed Momtaz Hosny, PhD
This document summarizes research on integrating fuzzy logic control with linear quadratic regulator (LQR) control for an aerial refueling autopilot. It describes modeling an aircraft, applying LQR control alone and with fuzzy logic control integrated. The integrated LQR fuzzy control is shown to more effectively suppress uncertainties and minimize mission time compared to LQR alone. Key aspects covered include aircraft modeling, optimal LQR flight control, applying fuzzy inference systems, deriving fuzzy rules, and the integrated LQR fuzzy control structure applied to pitch and lateral control for aerial refueling simulations.
To design and implementation of variable and constant with no load for induction motor (IM) that is the goal in this work. This paper was including three parts, first the simulation model with no load for IM, Second the simulation model with constant load for IM, Third the simulation model with variable load for IM. In addition, this work includes comparative between two different controllers (PI and fuzzy logic control (FLC). The simulation results clearly the implementation of variable and constant with no load for IM. The simulation response of the system achieves better results when choosing to use type fuzzy-PI controller technique comparison with conventional PI controller and improve the performance of the system at different operation conditions.
Adaptive PI Controller for Voltage Regulation in Power SystemsISA Interchange
Static synchronous compensator (STATCOM) provides the means to improve quality and reliability of a power system as it has the functional capability to handle dynamic disturbances, such as transient stability and power oscillation damping as well as to providing voltage regulation. In this paper, a robust adaptive PI-based optimal fuzzy control strategy is proposed to control a STATCOM used in distribution systems. The proposed intelligent strategy is based on a combination of a new General Type-II Fuzzy Logic (GT2FL) with a simple heuristic algorithm named Teaching Learning Based Optimization (TLBO) Algorithm. The proposed framework optimally tunes parameters of a Proportional-Integral (PI) controller which, similar to most of other researchers regarding control of STATCOM, are in charge of controlling the device. The proposed controller guaranties robustness and stability against uncertainties caused by external disturbances or ever-changing nature of the power systems. The TLBO optimizes the parameters of the controller as well as the input and output membership functions. To validate the efficiency of the proposed controller, the obtained simulation results are compared with those of the two most recent researches applied in this field, namely, conventional Proportional Integral (PI) controller and Optimal Fuzzy PI (OFPI) controller. Results demonstrate the successfulness and effectiveness of the proposed online-TLBO General Type-2 Fuzzy PI (OGT2FPI) controller and its superiority over conventional approaches.
IRJET- Optimum Design of PSO based Tuning using PID Controller for an Automat...IRJET Journal
This document discusses using particle swarm optimization (PSO) to tune the parameters of a PID controller for an automatic voltage regulator (AVR) system. The goal is to improve the system's transient performance by minimizing overshoot and steady state error. PSO is applied to optimize the proportional, integral, and derivative parameters of the PID controller. Simulation results show the PSO-tuned PID controller provides significantly better control of the AVR system compared to a traditionally tuned PID controller. The tuned controller gives faster response, lower overshoot, and improved stability when subjected to disturbances and parameter variations.
This document describes a PID controller with self-tuning capabilities using fuzzy logic. It replaces the conventional PID controller in a chopper-fed DC motor drive system to improve performance. The PID gains (KP, KI, KD) are automatically tuned online by a fuzzy logic controller based on the error and change in error. This allows the PID gains to adapt as needed for different operating conditions. Simulation results showed the proposed self-tuning PID controller performed better than a conventional PID controller.
Design Novel Nonlinear Controller Applied to Robot Manipulator: Design New Fe...Waqas Tariq
This document describes a novel adaptive feedback linearization fuzzy controller for robot manipulators. It begins by discussing limitations of traditional feedback linearization controllers, such as sensitivity to parameter uncertainty. It then proposes designing a feedback linearization fuzzy controller to address this issue. The key steps are: 1) designing the fuzzy controller, including fuzzifying inputs/outputs and developing a rule base, 2) developing an adaptive feedback linearization fuzzy controller by adding an adaptive law to tune fuzzy rule parameters online and improve disturbance rejection. The goal is to develop a robust position controller for robot manipulators that maintains acceptable performance despite nonlinearities and uncertainty.
This paper introduces experimental comparison study between six and four switch inverter fed three phase induction motor drive system. The control strategy of the drive is based on speed sensoreless vector control using model reference adaptive system as a speed estimator. The adaptive mechanism of speed control loop depends on fuzzy logic control. Four switch inverter conFigureurations reduces the cost of the inverter, the switching losses, the complexity of the control algorithms, interface circuits, the computation of real-time implementation, volume-compactness and reliability of the drive system. The robustness of the proposed model reference adaptive system based on four switch three-phase inverter (FSTPI) fed induction motor drive is verified experimentally at different operating conditions. Experimental work is carried using digital signal processor (DSP1103) for a 1.1 kW motor. A performance comparison of the proposed FSTP inverter fed IM drive with a conventional six switch three-phase inverter (SSTP) inverter system is also made in terms of speed response. The results show that the proposed drive system provides a fast speed response and good disturbance rejection capability. The proposed FSTP inverter fed IM drive is found quite acceptable considering its performance, cost reduction and other advantages features.
The aim of this paper is to prove that fuzzy logic algorithm is a suitable control technique for fast processes such as electrical machines. This theory has been experimented on different kinds of electrical machines such as stepping motors, dc motors and induction machines (with 6 phases) and the experimental results show that the proposed fuzzy logic algorithm is the most suitable control technique for electrical machines since this algorithm is not time consuming and it is also robust between plant parameters variations.
IRJET- Speed Control of Induction Motor using Hybrid PID Fuzzy ControllerIRJET Journal
This document presents a study on using a hybrid PID fuzzy controller with a BAT optimization algorithm to control the speed of an induction motor. It begins with background on PID controllers and fuzzy logic controllers. It then proposes using a BAT algorithm to select the Kp and Ki parameters of a PI controller to regulate motor speed. The results show that the proposed BAT-PID controller reduces speed fluctuations and settling time compared to a traditional PID controller. In conclusion, the hybrid fuzzy-PID controller with BAT optimization improves induction motor speed control.
Direct digital control scheme for controlling hybrid dynamic systems using AN...XiaoLaui
An Estimator Based Inverse Dynamics Controller (EBIDC), which utilizes an Artificial Neural Network (ANN) based state estimation scheme for nonlinear autonomous hybrid systems which are subjected to state disturbances and measurement noises that are stochastic in nature, is proposed in this paper. A salient feature of the proposed scheme is that it offers better state estimates and hence a better control of non-measurable state variables with a non linear approach in correcting the a priori estimates by avoiding statistical linearization involved in existing approaches based on derivative free estimation methods. Simulation results guarantees significant reduction in Integral Square Error (ISE) and standard deviation (σ) of error, between the controlled variable and set point and control signal computation time when compared with best existing related work based on Unscented Kalman Filter (UKF) and Ensembeled Kalman Filter (EnKF). Detailed analysis of the experimental results on real plant under different operating conditions such as servo and regulatory operations, initial condition mismatch, and different types of faults in the system, confirms robustness of proposed approach in these conditions and support the simulation results obtained. The main advantage of the proposed controller is that the control signal computation time is very much less than the selected sampling time of the process, so direct control of the plant is possible with this approach.
Clock Gating of Streaming Applications for Power Minimization on FPGA’sIRJET Journal
This document discusses using clock gating techniques to reduce power consumption in streaming applications implemented on FPGAs. It introduces a method to selectively disable clock signals to inactive parts of a circuit to minimize dynamic power. The technique can be automatically applied during synthesis of dataflow designs for streaming applications. Experimental results on an MPEG-4 video decoder demonstrated power reductions of up to 30% with no loss in throughput.
Implementation of closed loop control technique for improving the performance...IJERA Editor
this review paper presents closed loop control techniques for controlling the inverter working under different load or KVA ratings. The control strategy of the inverter must guarantee its output waveforms to be sinusoidal with fundamental harmonic. For this purpose, close loop current control strategies such as H∞ repetitive controller, dual closed-loop feedback control, Adaptive Voltage Control, SRFPI controller, Optimal Neural Controller, etc. have been used to meet the power quality requirements imposed by IEEE Interconnection Standards. Based on present scenario regarding energy crises, immediate action is the use of different renewable energy sources (RESs) . Out of RESs, solar is gaining more attention. It is very important to design and developed a system which should be efficient enough to utilize the extracted energy for different types of load and feeding of energy into utility grid. Since experimentation and comparison of such inverter models on hardware being relatively expensive, the latest computing tool like MATLAB are considered to be a better alternative to simulate the outcomes of such expensive systems. The proposed closed loop control technique for the inverter working under linear and nonlinear system will be implemented in MATLAB/SIMULINK working platform and results will be analyzed to check its benefits.
IRJET- Load Frequency Control of a Wind Integrated Power System using Convent...IRJET Journal
This document summarizes a research paper that proposes using a fuzzy proportional-integral-derivative (FPID) controller for load frequency control of a power system integrated with wind power. The system being studied is a four-area power system with each area containing wind, hydro, and thermal power plants. Simulation results show that the system with renewable energy sources gives better dynamic response when using an FPID controller compared to using a conventional PID controller. The FPID controller is able to better suppress frequency deviations caused by load and power fluctuations from the renewable energy sources.
Shale Gas Opportunities for ISA in North AmericaISA Interchange
This document discusses potential opportunities for the Instrumentation, Systems, and Automation Society (ISA) to become involved in the shale gas industry in North America. It proposes a 9-step process for ISA to explore one such opportunity around workforce development and education/training. The steps include developing an ISA value proposition customized for shale gas, assessing market opportunities in 3 shale basins, meeting with key regional stakeholders, and determining a champion within ISA to pursue an initial deal. The overall aim is to leverage ISA's expertise in educational standards and training to help accelerate workforce development for the shale gas industry through partnerships with regional organizations, oil and gas companies, and community colleges.
Simulation and stability analysis of neural network based control scheme for ...ISA Interchange
This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709–14] is presented.
Sufficient condition for stabilization of linear time invariant fractional or...ISA Interchange
This paper presents the stabilization problem of a linear time invariant fractional order (LTI-FO) switched system with order 1<q><21><q><2><q><21><q><2 based on the convex analysis and linear matrix inequality (LMI) is presented and proved. Then a single Lyapunov function, whose derivative is negative, is constructed based on the extremum seeking method. A sliding sector is designed for each subsystem of the LTI-FO switched system so that each state in the state space is inside at least one sliding sector with its corresponding subsystem, where the Lyapunov function found by the extremum seeking control is decreasing. Finally, a switching control law is designed to switch the LTI-FO switched system among subsystems to ensure the decrease of the Lyapunov function in the state space. Simulation results are given to show the effectiveness of the proposed VS controller.
Eliminating Difficult Start-ups with State Based ControlsISA Interchange
The document discusses challenges with starting up difficult processes and how total automation can help address these challenges. It notes that issues like operator error, aging workforces, variability in operator skills, and process complexity can prolong startups and cause errors. Total automation, where the entire startup process is automated using advanced control strategies, regulatory controls, and state logic, can reduce startup times by half to two-thirds and make the process more reliable and repeatable. It also discusses elements that make processes difficult to control, like small operating envelopes and multitasking requirements, and how automation can help maintain critical process boundaries.
Identification and real time position control of a servo-hydraulic rotary act...ISA Interchange
This paper presents a new intelligent approach for adaptive control of a nonlinear dynamic system. A modified version of the brain emotional learning based intelligent controller (BELBIC), a bio-inspired algorithm based upon a computational model of emotional learning which occurs in the amygdala, is utilized for position controlling a real laboratorial rotary electro-hydraulic servo (EHS) system. EHS systems are known to be nonlinear and non-smooth due to many factors such as leakage, friction, hysteresis, null shift, saturation, dead zone, and especially fluid flow expression through the servo valve. The large value of these factors can easily influence the control performance in the presence of a poor design. In this paper, a mathematical model of the EHS system is derived, and then the parameters of the model are identified using the recursive least squares method. In the next step, a BELBIC is designed based on this dynamic model and utilized to control the real laboratorial EHS system. To prove the effectiveness of the modified BELBIC’s online learning ability in reducing the overall tracking error, results have been compared to those obtained from an optimal PID controller, an auto-tuned fuzzy PI controller (ATFPIC), and a neural network predictive controller (NNPC) under similar circumstances. The results demonstrate not only excellent improvement in control action, but also less energy consumption.
Control chart pattern recognition using k mica clustering and neural networksISA Interchange
Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the input data is first clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA) and the K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks, and the radial basis function neural networks, are investigated. Using the experimental study, we choose the best classifier in order to recognize the CCPs. Simulation results show that a high recognition accuracy, about 99.65%, is achieved.
Integrating Analyzers with Automation Systems: Oil and Gas by David SchihabelISA Interchange
The document discusses how gas analyzers are integrated with automation systems for real-time control of oil and gas operations. It describes a system that currently produces 40,000 bbls of oil, 20,000 bbls of natural gas liquids, and 230 million standard cubic feet per day of natural gas. The quality of gas streams is maintained through real-time analysis of the permeate gas stream, as off-spec gas could shut down the entire production system. It also details a gas treating unit that removes CO2 from residue gas streams using analyzer results to control inlet and outlet blending valves for the single operating column.
Pre-processing of data coming from a laser-EMAT system for non-destructive te...ISA Interchange
Non destructive test systems are increasingly applied in the industrial context for their strong potentialities in improving and standardizing quality control. Especially in the intermediate manufacturing stages, early detection of defects on semi-finished products allow their direction towards later production processes according to their quality, with consequent considerable savings in time, energy, materials and work. However, the raw data coming from non destructive test systems are not always immediately suitable for sophisticated defect detection algorithms, due to noise and disturbances which are unavoidable, especially in harsh operating conditions, such as the ones which are typical of the steelmaking cycle. The paper describes some pre-processing operations which are required in order to exploit the data coming from a non destructive test system. Such a system is based on the joint exploitation of Laser and Electro-Magnetic Acoustic Transducer technologies and is applied to the detection of surface and sub-surface cracks in cold and hot steel slabs.
Robust design of a 2 dof gmv controller a direct self-tuning and fuzzy schedu...ISA Interchange
This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure–or simply GMV2DOF–within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani fuzzy GMV2DOF parameters scheduling technique based on analytical and physical interpretations from robustness analysis of the system. Both strategies are assessed by simulation and real plants experimentation environments composed of a damped pendulum and an under development wind tunnel from the Department of Automation and Systems of the Federal University of Santa Catarina.
Fault tolerant synchronization of chaotic heavy symmetric gyroscope systems v...ISA Interchange
In this paper, fault tolerant synchronization of chaotic gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control is investigated. Taking the general nature of faults in the slave system into account, a new synchronization scheme, namely, fault tolerant synchronization, is proposed, by which the synchronization can be achieved no matter whether the faults and disturbances occur or not. By making use of a slave observer and a Lyapunov rule-based fuzzy control, fault tolerant synchronization can be achieved. Two techniques are considered as control methods: classic Lyapunov-based control and Lyapunov rule-based fuzzy control. On the basis of Lyapunov stability theory and fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic synchronization are obtained. The fuzzy rules are directly constructed subject to a common Lyapunov function such that the error dynamics of two identical chaotic motions of symmetric gyros satisfy stability in the Lyapunov sense. Two proposed methods are compared. The Lyapunov rule-based fuzzy control can compensate for the actuator faults and disturbances occurring in the slave system. Numerical simulation results demonstrate the validity and feasibility of the proposed method for fault tolerant synchronization.
Robust sdre filter design for nonlinear uncertain systems with an h performan...ISA Interchange
In order to remedy the effects of modeling uncertainty, measurement noise and input disturbance on the performance of the standard state-dependent Riccati equation (SDRE) filter, a new robust H∞H∞ SDRE filter design is developed in this paper. Based on the infinity-norm minimization criterion, the proposed filter effectively estimates the states of nonlinear uncertain system exposed to unknown disturbance inputs. Moreover, by assuming a mild Lipschitz condition on the chosen state-dependent coefficient form, fulfillment of a modified H∞H∞ performance index is guaranteed in the proposed filter. The effectiveness of the robust SDRE filter is demonstrated through numerical simulations where it brilliantly outperforms the conventional SDRE filter in presence of model uncertainties, disturbance and measurement noise, in terms of estimation error and region of convergence.
Modified smith predictor based cascade control of unstable time delay processesISA Interchange
An improved cascade control structure with a modified Smith predictor is proposed for controlling open-loop unstable time delay processes. The proposed structure has three controllers of which one is meant for servo response and the other two are for regulatory responses. An analytical design method is derived for the two disturbance rejection controllers by proposing the desired closed-loop complementary sensitivity functions. These two closed-loop controllers are considered in the form of proportional–integral-derivative (PID) controller cascaded with a second order lead/lag filter. The direct synthesis method is used to design the setpoint tracking controller. By virtue of the enhanced structure, the proposed control scheme decouples the servo response from the regulatory response in case of nominal systems i.e., the setpoint tracking controller and the disturbance rejection controller can be tuned independently. Internal stability of the proposed cascade structure is analyzed. Kharitonov’s theorem is used for the robustness analysis. The disturbance rejection capability of the proposed scheme is superior as compared to existing methods. Examples are also included to illustrate the simplicity and usefulness of the proposed method.
Real Time Optimization of Air Separation PlantsISA Interchange
In this presentation, the important aspects of an RTO application on air separation will be discussed including
the general IT structure, functions of its different software components, important steps in completing
such a project, challenges in optimization and corresponding solutions.
Bilateral control of master slave manipulators with constant time delayISA Interchange
This paper presents a novel teleoperation controller for a nonlinear master–slave robotic system with constant time delay in communication channel. The proposed controller enables the teleoperation system to compensate human and environmental disturbances, while achieving master and slave position coordination in both free motion and contact situation. The current work basically extends the passivity based architecture upon the earlier work of Lee and Spong (2006) [14] to improve position tracking and consequently transparency in the face of disturbances and environmental contacts. The proposed controller employs a PID controller in each side to overcome some limitations of a PD controller and guarantee an improved performance. Moreover, by using Fourier transform and Parseval’s identity in the frequency domain, we demonstrate that this new PID controller preserves the passivity of the system. Simulation and semi-experimental results show that the PID controller tracking performance is superior to that of the PD controller tracking performance in slave/environmental contacts.
Natural gas operations considerations on process transients design and controlISA Interchange
This manuscript highlights tangible benefits deriving from the dynamic simulation and control of operational transients of natural gas processing plants. Relevant improvements in safety, controllability, operability, and flexibility are obtained not only within the traditional applications, i.e. plant start-up and shutdown, but also in certain fields apparently time-independent such as the feasibility studies of gas processing plant layout and the process design of processes. Specifically, this paper enhances the myopic steady-state approach and its main shortcomings with respect to the more detailed studies that take into consideration the non-steady state behaviors. A portion of a gas processing facility is considered as case study. Process transients, design, and control solutions apparently more appealing from a steady-state approach are compared to the corresponding dynamic simulation solutions.
Design and analysis of a model predictive controller for active queue managementISA Interchange
Model predictive (MP) control as a novel active queue management (AQM) algorithm in dynamic computer networks is proposed. According to the predicted future queue length in the data buffer, early packets at the router are dropped reasonably by the MPAQM controller so that the queue length reaches the desired value with minimal tracking error. The drop probability is obtained by optimizing the network performance. Further, randomized algorithms are applied to analyze the robustness of MPAQM successfully, and also to provide the stability domain of systems with uncertain network parameters. The performances of MPAQM are evaluated through a series of simulations in NS2. The simulation results show that the MPAQM algorithm outperforms RED, PI, and REM algorithms in terms of stability, disturbance rejection, and robustness.
DC servomechanism parameter identification a closed loop input error approachISA Interchange
This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control law employed for closing the loop. The model contains four parameters that depend on the servo inertia, viscous, and Coulomb friction as well as on a constant disturbance. Lyapunov stability theory permits assessing boundedness of the signals associated to the identification algorithm. Experiments on a laboratory prototype allows evaluating the performance of the approach.
Efficient decentralized iterative learning tracker for unknown sampled data i...ISA Interchange
In this paper, an efficient decentralized iterative learning tracker is proposed to improve the dynamic performance of the unknown controllable and observable sampled-data interconnected large-scale state-delay system, which consists of NN multi-input multi-output (MIMO) subsystems, with the closed-loop decoupling property. The off-line observer/Kalman filter identification (OKID) method is used to obtain the decentralized linear models for subsystems in the interconnected large-scale system. In order to get over the effect of modeling error on the identified linear model of each subsystem, an improved observer with the high-gain property based on the digital redesign approach is developed to replace the observer identified by OKID. Then, the iterative learning control (ILC) scheme is integrated with the high-gain tracker design for the decentralized models. To significantly reduce the iterative learning epochs, a digital-redesign linear quadratic digital tracker with the high-gain property is proposed as the initial control input of ILC. The high-gain property controllers can suppress uncertain errors such as modeling errors, nonlinear perturbations, and external disturbances (Guo et al., 2000) [18]. Thus, the system output can quickly and accurately track the desired reference in one short time interval after all drastically-changing points of the specified reference input with the closed-loop decoupling property.
ENERGY MODELING OF THE PYROPROCESSING OF CLINKER IN A ROTARY CEMENT KILNISA Interchange
This paper highlights the efforts taken by the author in developing an Energy Model for the pyro-processing of Clinker production in a dry-process rotary cement kiln. In this paper this Energy Model is applied to a state of the art cement plant in a Far East Asian country. However this Energy Model is also applicable to all the modern dry process cement kilns. This model is based on actual field input data and site observations.
Decentralized proportional-integral controller based on dynamic decoupling t...IJECEIAES
An improved technique for the design of decentralized dynamic decoupled proportional-integral (PI) controllers to control many variables of column flotation was developed and implemented in this paper. This work was motivated by challenges when working with multiple inputs and multiple outputs (MIMO) systems that are not controllable by conventional linear feedback controllers. Conventional feedback control design consists of various drawbacks when it comes to complex industrial processes. The introduction of decentralization, decoupling, and many advanced controls design methods overcomes these drawbacks. Hence, the design and implementation of control systems that mitigate stability for MIMO systems are important. The developed closed-loop model of the flotation process is implemented in a real-time platform using TwinCAT 3.1 automation software and CX5020 Beckhoff programmable logic controllers (PLC) through the model transformation technique. The reasons for using the CX5020 as an implementation environment were motivated by the reliability, and is built according to new industry standards, allowing transformation, which makes it more advantageous to be used more than any other PLCs. This is done to validate the effectiveness of the recommended technique and prove its usability for any multivariable system. Comparable numerical results are presented, and they imply that industrial usage of this method is highly recommended.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Decentralised PI controller design based on dynamic interaction decoupling in...IJECEIAES
An enhanced method for design of decenralised proportional integral (PI) controllers to control various variables of flotation columns is proposed. These columns are multivariable processes characterised by multiple interacting manipulated and controlled variables. The control of more than one variable is not an easy problem to solve as a change in a specific manipulated variable affects more than one controlled variable. Paper proposes an improved method for design of decentralized PI controllers through the introduction of decoupling of the interconnected model of the process. Decoupling the system model has proven to be an effective strategy to reduce the influence of the interactions in the closed-loop control and consistently to keep the system stable. The mathematical derivations and the algorithm of the design procedure are described in detail. The behaviour and performance of the closed-loop systems without and with the application of the decoupling method was investigated and compared through simulations in MATLAB/Simulink. The results show that the decouplers - based closedloop system has better performance than the closed-loop system without decouplers. The highest improvement (2 to 50 times) is in the steady-state error and 1.2 to 7 times in the settling and rising time. Controllers can easily be implemented.
Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input–multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer.
Quasi-Static Evaluation of a Modular and Reconfigurable Manufacturing CellHillary Green
This document presents a novel modular and reconfigurable manufacturing cell (MRMC) system that aims to provide flexible manufacturing capabilities. Some key points:
- The MRMC system consists of modular manipulation hardware and software that can be quickly configured and reconfigured for different assembly and packaging applications.
- It uses a unique interconnect design to allow mechanical and electrical connection between modules. Distributed intelligence and self-locating software enables automatic configuration.
- Analytical evaluation of precision shows the MRMC maintains necessary accuracy and repeatability for tasks like pick-and-place despite reconfiguration.
- The goal is to offer a low-cost, low-risk solution for prototyping and low-volume manufacturing through
A hybrid bacterial foraging and modified particle swarm optimization for mode...IJECEIAES
This paper study the model reduction procedures used for the reduction of large-scale dynamic models into a smaller one through some sort of differential and algebraic equations. A confirmed relevance between these two models exists, and it shows same characteristics under study. These reduction procedures are generally utilized for mitigating computational complexity, facilitating system analysis, and thence reducing time and costs. This paper comes out with a study showing the impact of the consolidation between the Bacterial-Foraging (BF) and Modified particle swarm optimization (MPSO) for the reduced order model (ROM). The proposed hybrid algorithm (BF-MPSO) is comprehensively compared with the BF and MPSO algorithms; a comparison is also made with selected existing techniques.
DEVELOPMENT OF MULTI INPUT MULTI OUTPUT COUPLED PROCESS CONTROL LABORATORY TE...IAEME Publication
Multi Input – Multi Output (MIMO) processes are very commonly found in many chemical unit processes. Control of such MIMO processes is always challenging due to coupling between inputs and outputs. Even after very significant efforts made by the research fraternity, control of coupled MIMO process is still an open research issue. Computerized and easy to use laboratory scale set up is very essential to investigate performance of different control algorithm on MIMO process. An attempt is made to develop low cost, configurable, computerized and smaller size multi input multi output coupled process control laboratory test setup.
Analysis and implementation of local modular supervisory control forIAEME Publication
1. The document describes the analysis and implementation of a local modular supervisory control system for a manufacturing cell using programmable logic controllers (PLCs).
2. A local modular approach is used where modular supervisors are obtained for each behavioral specification by considering only locally affected subsystems, avoiding state space explosion.
3. The modular supervisors are implemented on the PLC in a three-level structure that executes the supervisors concurrently and interfaces them to the physical system.
Test platform for electronic control units of high-performance safety-critica...IJECEIAES
In this paper we are mostly concerned with the problem of testing electronic control units of synchronized electric power actuators. This task is particularly complex for safety critical applications, where it is crucial that the control system properly reacts in response to the faults that are hard to reproduce and verify. A cost-effective flexible and reconfigurable test platform is proposed, discussing its architecture and implementation. The proposed system facilitates the phase of definition and development of the electronic control unit, allowing the interfacing towards both hydraulic and electromechanical actuators, and having a high flexibility as regards the I/O signals. Some results, obtained during the laboratory test activity, are also presented.
IRJET - Effect of Changing Membership Functions in the Operation of Fuzzy Con...IRJET Journal
This document discusses the effect of changing membership functions in fuzzy logic controllers for flexible AC transmission system (FACTS) devices in power systems. It analyzes the performance of three FACTS controllers - static synchronous series compensator (SSSC), static VAR compensator (SVC), and unified power flow controller (UPFC) - with fuzzy logic controllers using different membership functions. The document presents simulation results from MATLAB/Simulink that compare the system response for each FACTS controller with conventional control versus fuzzy control, and with fuzzy controllers using triangular, trapezoidal, Gaussian, and generalized bell-shaped membership functions. The results show that fuzzy control of FACTS devices provides better damping of power oscillations compared to conventional control, and that triangular
Induction motors are work-horse of the industry and major element in energy conversion. The replacement of the existing non-adjustable speed drives with the modern variable frequency drives would save considerable amount of electricity. A proper control scheme for variable frequency drives can enhance the efficiency and performance of the drive. This paper attempt to provide a rigorous review of various control schemes for the induction motor control and provides critical analysis and guidelines for the future research work. A detailed study of sensor based control schemes and sensor-less control schemes has been investigated. The operation, advantages, and limitations of the various control schemes are highlighted and different types of optimization techniques have been suggested to overcome the limitations of control techniques.
A resonable approach for manufacturing system based on supervisory control 2IAEME Publication
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Design of a Controller for Systems with Simultaneously Variable Parametersijtsrd
The contribution of this paper is in suggesting an analysis and design of a control system with variable parameters By applying the recommended by the author method of the Advanced D-partitioning the system's stability can be analyzed in details The method defines regions of stability in the space of the system's parameters The designed controller is enforcing desired system performance The suggested technique for analysis and design is essential and beneficial for the further development of control theory in this area Prof. Kamen Yanev "Design of a Controller for Systems with Simultaneously Variable Parameters" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18440.pdf
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Evaluation of standby power system architecturesmichaeljmack
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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2. O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140 133
The overall control architecture consists of a bank of controllers
(multi-controllers), and a supervisor. At each time instant, a high
level decision maker, the so called supervisor, determines which
controller should be placed in the feedback loop. In other words,
when estimates of the plant are changed, a new controller may
be selected, which is similar to the idea of adaptive control. But
unlike the traditional adaptive control strategies, this adaptation
takes place in a discrete fashion.
One of the main advantages of the supervisory control is
its modularity. Designing multi-estimators, multi-controllers, and
switching logic can be done in a mutually independent manner.
This feature enables the designer, to use ‘‘off-the-shelf’’ robust
control laws [9]. The objective of this paper is to provide a
practical solution to the problem of decentralized control of
uncertain multivariable plants with variable control configuration.
Decentralized MIMO-QFT is used as the underlying linear robust
design strategy, because it is a powerful design methodology that
provides a transparent tradeoff between different, often conflicting
design specifications, and suggests a controller with minimum cost
of feedback that satisfies the set of performance specifications in
spite of the plant uncertainty [13]. However, as with any other
linear robust design methodology, it fails in the face of variable
control configuration. By combining and switching robust designs,
the designed controller optimizes the time response of the plant by
fast adaptation of the controller parameters during the transient
response based on the error amplitude and ensures closed loop
stability [14].
The problem of robust adaptive control via combining QFT
and switching supervisory control is introduced in [15] for single-
input–single-output (SISO) plants; the entire region of uncertainty
is partitioned into smaller regions. For each region, a QFT
controller is employed to attain robust stability and performance
despite uncertainties and disturbances. A supervisory architecture
orchestrates controller selection. This selection is based on the
values of monitoring signals. In this paper, the combined switching
QFT control is extended for multi-input–multi-output (MIMO)
plants. The key idea is to divide the original uncertainty set
into smaller subsets with certain control configuration as in [16].
Then, for each uncertainty subset, a decentralized MIMO QFT
control is worked out to satisfy the robust stability and tracking
requirements. Finally, a switching supervisory structure is used to
recognize to which uncertainty subset, the ‘‘real’’ uncertain plant
is matched with. Then, the supervisor places the corresponding
controller in the feedback loop.
This paper is organized as follows. In Section 2, switching
supervisory control is briefly reviewed. Fundamentals of MIMO-
QFT are given in Section 3. Our proposed design structure is
described in Section 4. Simulation results and conclusions are
made in Sections 5 and 6, respectively.
2. Switching supervisory control
In this section, the supervisory control framework for adap-
tively controlling plants with large uncertainty is briefly re-
viewed [11,12]. The basic idea is to divide the uncertainty set,
which is compact, into a finite number of subsets with nominal val-
ues and then employ a family of controllers, one for each nominal
value. Switching among the controllers is orchestrated by a super-
visor in such a way that closed-loop stability is assured, as is shown
in Fig. 1. The benefits gained by this approach include (i) simplicity
and modularity in design: controller design amounts to controller
design for linear time-invariant plants with smaller uncertainty,
for which various computationally efficient controller design tools
are available; (ii) ability to handle larger classes of plants than is
possible with other approaches (see [9] for more discussion).
Fig. 1. The supervisory control framework.
Consider an uncertain linear plant Mp parameterized by a
parameter p, and denote by p∗
the true but unknown parameter.
The corresponding realization is:
Mp∗ :
˙x = Ap∗ x + Bp∗ u
y = Cp∗ x,
(1)
where x ∈ Rnx
is the state, u ∈ Rnu
is the input, and y ∈ Rny
is
the output. The parameter p∗
∈ Rnp
belongs to a known finite set
P := {p1, . . . , pm}, where m is the cardinality of P.
It is assumed that (Ap, Bp) is stabilizable and (Ap, Cp) is
detectable for every p ∈ P.
The architecture of supervisory adaptive control comprises: (1)
a family of controllers, and (2) a decision maker (supervisory unit).
The decision maker, consisting of a multi-estimator, a monitoring
signal generator and a switching logic, produces a switching signal
that indicates at every time the active controller.
• Multi-estimator: A multi-estimator is a collection of models, one
for each fixed parameter p ∈ P. The multi-estimator takes in
the input u and produces a bank of outputs yp, p ∈ P. The
multi-estimator should have the following matching property:
there is ˆp ∈ P such that
|yˆp(t) − y(t)| ≤ cee−λe(t−t0)
|yˆp(t0) − y(t0)| (2)
for all t ≥ t0, for all u, and for some ce ≥ 0 and λe > 0. One
such multi-estimator for (1) is constructed as follows with the
state xE = (ˆxT
1 , . . . , ˆxT
m)T
where xE ∈ Rm×nx
and, the dynamics
˙ˆxp = Ap ˆxp + Bpu + Lp(yp − y),
yp = Cp ˆxp,
(3)
for all p ∈ P, and the property (2) is satisfied with ˆp = p∗
. The
matrices Lp in (3) are such that Ap + LpCp are Hurwitz
∀p ∈ P. (since (3) with p = p∗
and (1)
imply that (d/dt)(xp∗ − x) = (Ap + LpCp) (xp∗ − x)
and y = Cp∗ x).
• Multi-controller: A family of candidate controllers {Gp} is
designed such that the closed loop plant meets the desired
robust stability and performance specifications for every p ∈ P .
Then the family of controllers is
Gp, p ∈ P. (4)
• Monitoring signals: Monitoring signals µp, p ∈ P are norms of
the output estimation errors, ep = yp − y. Here, the monitoring
signals are generated as
µp := ε0 +
∫ t
0
e−λ(t−s)
γ ‖yp(s) − y(s)‖2
ds (5)
for some γ , ε0 > 0 and λ ∈ (0, λ0), where ‖.‖ denotes the
vector norm. The numbers γ , ε0, and λ are design parameters,
and λ0 is related to the eigenvalues of the closed-loop plant (for
3. 134 O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140
Fig. 2. The two-degrees of freedom structure of QFT.
details on λ0, see [11]). Note that the interactions between the
outputs of the multivariable plant are taken into account in the
estimation error vector.
• Switching logic: The switching signal, which nominates the
active controller at each time instant, is produced by the scale
independent hysteresis switching logic [17]:
σ(t) :=
argmin
q∈P
µq(t) if ∃q ∈ P such that
(1 + h)µq(t) ≤ µσ(t−)(t)
σ(t−
) else,
(6)
where h > 0 is called a hysteresis constant and is a design
parameter that conveniently prevents excessive switching. The
control signal applied to the plant is u(t) = uσ (t). (See Fig. 1.)
3. Decentralized quantitative feedback design
The decentralized MIMO-QFT design technique provides a
design procedure to synthesize a fixed diagonal controller transfer
function matrix G(s) and pre-filter F(s) to satisfy specifications on
the closed-loop plant shown in Fig. 2, where P(s) is the MIMO
uncertain plant.
In solving an n × n multivariable design problem, the
synthesis problem is converted into n equivalent single-loop
multi-input–single-output (MISO) problems, where parameter
uncertainties, external disturbances and performance tolerances
are derived from the original problem, and the coupling effects
between MISO subsystems are treated as disturbance inputs. The
objective of the design is to achieve set point tracking, while
minimizing the outputs due to the disturbance inputs (cross-
coupling effects) [13]. It is desired that the closed-loop system is
stable and:
|tij(jω)| ≤ bij(ω), i ̸= j,
0 ≤ aii(ω) ≤ |tii(jω)| ≤ bii(ω),
(7)
where T(s) = [tij(s)] is the control ratio matrix, (note that the
closed-loop plant control ratio tij = yi/rj relates the ith output to
the jth input.) A(s) = [aij(s)] and B(s) = [bij(s)] are the desired
lower and upper tracking bounds for the MIMO plant.
4. Switching supervisory QFT control
Combining switching and QFT for SISO plants was first
introduced in [14] to prioritize some specifications over others
according to the state of the plant at each time. Switching is used to
select the appropriate controller which is determined based on the
error amplitude. However, the proposed method in [14] requires
that the underlying controllers must have the same poles and this
constraint, limits controllers type and therefore the performance
of the plant. A more general approach for SISO plants is introduced
in [15] to overcome this limitation in which the quantitative
feedback design was used in the context of switching supervisory
adaptive control to achieve robust stability and performance for
highly uncertain SISO plants. In the following, the decentralized
switching-QFT method is given for MIMO plants based on the
SISO version of [15]. It is shown that the proposed method could
be implemented for complex uncertain plants with I/O pairing
Fig. 3. The supervisory based switching QFT control architecture.
or control configuration changes during the multivariable plant
operation.
In the proposed method, the idea is to divide the original
uncertainty set into smaller subsets with certain I/O pairing.
Then, for each uncertainty subset a decentralized MIMO QFT
control is worked out to satisfy the robust stability and tracking
requirements. Finally, a switching supervisory structure as shown
in Fig. 3 is used to match the proper uncertainty subset to the ‘‘real’’
uncertain plant. Then, the supervisor places the corresponding
controller in the feedback loop.
4.1. Problem formulation
Regarding highly uncertain MIMO plants, two distinct cases
may occur:
• A single decentralized QFT controller exists for the entire
uncertainty set. However, the closed loop performance may not
be improved further as desired.
• A single decentralized QFT controller does not exist to ensure
closed loop robust stability and performance.
The second case is more severe, especially in cases where
parameter uncertainty can lead to input–output pairing change
which is detrimental to the decentralized control of multivariable
plants. The goal is to design a stable closed-loop control system
which can track a predetermined set point in spite of large plant
uncertainty and/or disturbances.
4.2. Class of admissible plants
The plant is assumed to be modeled by a stabilizable and
detectable MIMO linear plant with control input u and measured
output y, perturbed by a bounded disturbance input d. It is
assumed that the plant transfer function belongs to a known class
of admissible transfer function matrices of the form:
M :=
p∈P
Mp
where p is a parameter taking values in some index set. Mp
is also a family of transfer functions ‘‘centered’’ around some
known nominal process model transfer function νp [18]. Allowable
unmodeled dynamics around the nominal process model transfer
functions νp could be specified as:
Mp :=
νp(1 + δm) + δa : ‖δm‖∞,λ ≤ ε, ‖δa‖∞,λ ≤ ε
,
where ε > 0 and λ ≥ 0 are two arbitrary numbers. Here, ‖.‖∞,λ
denotes eλt
-weighted H∞ norm of a transfer function matrix:
4. O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140 135
‖v‖∞,λ := supRe[s]≥0 ¯σ(v(s −λ)), ( ¯σ(.): the peak of the maximum
singular value) [18].
Throughout the paper, we will take P to be a compact subset of
a finite-dimensional normed linear vector space.
By this definition, the entire region of plant uncertainty is
partitioned into a set of smaller regions. Each smaller region is
presented by a parameter value p, and Mp is a model of the plant
in that small region.
Considering all permissible uncertainties and disturbances in
each smaller region, based on the appropriate I/O pairing, a
decentralized MIMO-QFT controller is designed to achieve robust
stability and robust set point tracking specifications.
4.3. Multi-estimator and multi-controller
A state-shared multi-estimator of the following form could be
utilized here.
˙xE = AE xE + LE y + BE u, yp = CpxE , ep = yp − y, (8)
where p ∈ P, and AE is an asymptotically stable matrix. This type
of structure is quite common in adaptive control [19]. One option
for AE , LE and BE is as follows (using the multi-estimators described
in (3)):
xE = (ˆxT
1 , . . . , ˆxT
m)T
, AE = diag[Ap + LpCp],
LE = block diag[−Lp], BE = block diag[Bp], p ∈ P.
For practical reasons, the bank of local controllers can be
efficiently implemented (multirealized) by means of a state-shared
parameter dependent feedback system. The method provided can
implement bumpless transfer, which is an effective way to improve
poor transient response of the switched systems [20,21].
4.4. Bumpless transfer using multirealization techniques
A major problem in the practical implementation of switching
based control strategies is the undesirable transient behavior of the
plant outputs during switching times. The key response property
that can guarantee a smooth transition during the switching times
is the bumpless transfer [20]. That is, control input u must be
continuous even in the time instants at which the supervisor
changes the controller. By bumpless transfer, the control signal is
smooth and there is no need to apply sudden changes to system
inputs by actuators, while unexpected changes in the control signal
can yield undesirable transient responses in switching times.
On the other hand, in a multicontroller architecture, only
one of the controllers at any instant of time is placed into the
feedback loop. Hence, at each time instant it is only necessary to
generate one control signal. This can be employed to simplify the
multicontroller architecture by generating all control signals by
a single controller. This concept is commonly identified as state
sharing [20]. State sharing can also be used in the multiestimation
part of switching multiple model control methods [19].
The state-shared implementation for a family of multivariable
LTI controllers with strictly proper transfer function matrices using
the right matrix function description (MFD) with denominator
matrix in the Popov form is presented in [21], in the form of
{A0 + B0Ki, B0, Ci} or its dual realization {A0 + LiC0, Bi, C0} (i =
1, 2, . . . , m). The multirealization form {A0 + LiC0, Bi, C0} is
preferred for the implementation of multicontroller structures
to achieve bumpless transfer. However, it is more convenient to
investigate the dual form {A0 + B0Ki, B0, Ci} because of the results
on invariant description of linear multivariable plants [22]. All
controller transfer function matrices can be written in the form of
a right MFD in which all the denominator matrices are in the Popov
form. Based on the results in [21], a modified and simpler algorithm
is presented in [23], which uses the Hermite form polynomial
matrix to achieve a multirealization in the form of {A0 +Ai, B0, Ci}.
In this multirealization form, A0 is a stable matrix and (A0, B0)
is controllable. Also, to achieve bumpless transfer, the duality
property can be employed to obtain a multirealization in the form
{A0 +Ai, Bi, C0}. In the following, the method based on the Hermite
form polynomial matrix to achieve a multirealization in the form
of {A0 + Ai, B0, Ci} is briefly reviewed.
A given n×n nonsingular polynomial matrix can be transformed
to a unique row Hermite form DH (s) by elementary column
operations, where DH (s) is an upper triangular polynomial matrix
with each diagonal element monic and of higher degree than any
other element in the same row, if a diagonal element is 1, all other
entries in that row will be zero [24]. With a unique denominator
DH (s) in the row Hermit form polynomial matrix, a unique and
canonical right MFD for H(s) = NH (s)D−1
H (s) is obtained and is
called the row Hermite form MFD.
In general, we can always write a given polynomial matrix D(s)
in the following form:
D(s) = SL(s)Dhr + ΨL(s)Dlr
where SL(s) = diag{sli , ı = 1, 2, . . . , n}, and li is the degree
of the ith row of D(s). Moreover, Dhr is the highest-row-degree
coefficient matrix of D(s) and the term ΨL(s)Dlr accounts for the
lower-row-degree terms of D(s), with Dlr a matrix of coefficients
and ΨL(s) = block diag{[sli−1
, sli−2
, . . . , 1], i = 1, 2, . . . , n} [24].
Theorem 1 ([23]). Consider a polynomial matrix DH (s) which is in
row Hermite form. Let li denote the degree of the ith row of DH (s)
and µi is the controllability index corresponding to the ith column of
a matrix B (µi independent vectors bi, Abi, . . . , Aµi−1
bi), where (A, B)
is a controllable pair that corresponds to a state realization of D−1
H (s).
Then,
µi = li.
Theorem 2 ([23]). Consider a set of ni-input no-output strictly
proper systems Hi(s) (i = 1, 2, . . . , m). There exist a set of realiza-
tions in the canonical controllability form {Ai, B0, Ci} where Ai is an
n×n matrix and {Ai, B0, Ci} are controllable realizations of Hi(s) (i =
1, 2, . . . , m) if and only if there exists a right row Hermite form MFD
for all Hi(s), with Hi(s) = NHi
(s)D−1
Hi
(s), and deg{DHi
(s)} = n for
i = 1, 2, . . . , m, provided that
lik = ljk, i, j = 1, 2, . . . , m and k = 1, 2, . . . , ni
where lik is the degree of the kth row of the DHi
(s).
Based on Theorem 2, the following algorithm is given to obtain
the multirealization in the form of {A0 + Ai, B0, Ci}.
The Multirealization algorithm:
Step 1. Write irreducible row Hermite form MFD descriptions for
all the MIMO systems Hi(s) = NHi
(s)D−1
Hi
(s).
Step 2. Let lmaxj = maxi lij, where lij denotes the degree of the jth
column in DHi
(s). Then, for all DHi
(s) matrices, multiply the
jth column by (s + a)lmaxj − lij for arbitrary chosen a > 0.
Step 3. Applying changes in the previous steps, it may be possible
that DHi
(s) is not in the row Hermite form. Convert all DHi
(s)
to the row Hermite form and apply appropriate changes on
NHi
(s) to have Hi(s) unchanged (Hi(s) = ˜NHi
(s)˜D−1
Hi
(s)).
Step 4. Using the controllable canonical form realization for
systems Hi(s) = ˜NHi
(s)˜D−1
Hi
(s), (i = 1, 2, . . . , m), the
multirealization in the {A0 + Ai, B0, Ci} form is obtained.
In the following section, the proposed algorithm is used
for practical implement of the bank of controllers. Instead of
switching between different controller transfer function matrices,
a multirealization of these controllers is employed. In the first
5. 136 O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140
Table 1
Plant conditions used in Example 1.
No. γ11 γ22 γ12 γ21 δ11 δ22 δ12 δ21
1 1 2 0.5 1 1 2 2 3
2 1 2 0.5 1 0.5 1 1 2
3 1 2 0.5 1 0.2 0.4 0.5 1
4 1 2 4 5 2 3 1 2
5 1 2 4 5 1 2 0.5 1
6 1 2 4 5 0.5 1 0.2 0.4
7 10 8 2 4 1 2 2 3
8 10 8 2 4 0.5 1 1 2
9 10 8 2 4 0.2 0.4 0.5 1
10 5 8 16 20 2 3 1 2
11 5 8 16 20 1 2 0.5 1
12 5 8 16 20 0.5 1 0.2 0.4
step, the multirealization algorithm is applied to the transpose of
transfer function matrices, HT
i (s). Then, using the duality theorem,
the multirealization in the {A0 +Ai, Bi, C0} form is obtained. Finally,
the controller with the bumpless transfer property is implemented
using this multirealization technique.
5. Simulation results
Example 1. In this section, a numerical example is used to
illustrate the proposed design method. Consider the following 2×2
uncertain plant:
M(s) =
γ11
1 + sδ11
γ12
1 + sδ12
γ21
1 + sδ21
γ22
1 + sδ22
.
The corresponding twelve different parameter cases are given
in Table 1.
The complexity of this example lies in the fact that the
appropriate input–output pair changes as the parameters vary
and a single robust decentralized controller (regardless of the
underlying design methodology) cannot effectively control the
plant.
Closed loop specifications (for all plants)
(1)—The tracking specifications, Tlij ≤ |T(jω)|ij ≤ Tuij (i, j =
1, 2.) are basically non-interacting, and are enforced to ω ≤ ωh =
10 rad/s.
On-diagonal:
Tuii(ω) =
25
s2 + 6s + 25
s=jω
and
Tlii(ω) =
4
s2 + 4.4s + 4
s=jω
.
Off-diagonal:
Tuij(ω) = 0.1, and Tlij = 0.
(2)—Stability margin: |1(1 + Li)| ≤ 3.5 dB for all plants.
Where Li corresponds to the ith loop gain and this would
indicate a gain margin and phase margin of 9.6 dB and 39 deg
respectively [13].
The relative gain array (RGA) was introduced by Bristol [2]
as a measure of interaction in multivariable control plants and
is a practical tool for control configuration selection in many
multivariable plants. The RGA is defined as
Λ = M(0)∗
M−T
(0),
where the asterisk denotes the Schur product and −T is the inverse
transpose.
The elements of the RGA for the uncertain process M(s) is as
follows:
Λ =
[
λ 1 − λ
1 − λ λ
]
, λ =
γ11γ22
γ11γ22 − γ12γ21
.
Fig. 4. Variations of the plant parameters.
Fig. 5. Switching signal, note that the change in RGA matrix is recognized by
supervisor.
For cases 1–3, λ = 1.33; therefore, pairing along the diagonal is
proposed. In cases 4–6, the structural change in the multivariable
plant clearly leads to λ = −0.11 and the off diagonal input–output
pairing is proposed.
If a fixed structure decentralized controller is employed, the
parameter variation leads to closed-loop instability. However, in
the case of a switching supervisory control design methodology
shown in Fig. 3, the change in the RGA matrix resulting from
the plant parameter variations, shown in Fig. 4, is recognized
by the supervisor as shown in Fig. 5. Hence, when the change
has occurred, a new input–output pairing is chosen. Fig. 6 shows
that the decentralized switching-QFT controller can easily handle
the new control configuration. The corresponding control effort is
shown in Fig. 7.
For cases 7–9, λ = 1.11 where diagonal pairing is the appropri-
ate input–output pair.
Finally, in cases 10–12, λ = −0.14 which leads to the off
diagonal input–output pairing.
In order to design the multiple-model based decentralized
switching-QFT architecture, the region of uncertainty is divided
into the following smaller regions:
Cases 1, 2 and 3
Cases 4, 5 and 6
Cases 7, 8 and 9
Cases 10, 11 and 12.
6. O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140 137
Fig. 6. Plant outputs in the proposed switching structure. (The family of controllers
are implemented using multirealization technique to achieve bumpless transfer.)
Fig. 7. Control inputs in the proposed switching structure. (The family of
controllers are implemented using multirealization technique to achieve bumpless
transfer.)
Tank 3
Pump 1
1ν
Pump 1
2ν
1
y
2
y
Tank 1
Tank 4
Tank 2
Fig. 8. Schematic diagram of the quadruple-tank process.
Now, for each region, a decentralized MIMO-QFT design is
employed to attain robust stability and performance in spite of
uncertainties and disturbances.
The decentralized controllers and pre-filters are designed as
follows:
G1(s) =
185(s + 1.1)
s(s + 13.5)
0
0
10(s + 1.4)
s(s + 5.3)
,
F1(s) =
6
s + 6
0
0
5.8
s + 5.8
G2(s) =
0
57.9(s + 2.9)
s(s + 21.7)
38.4(s + 1.7)
s(s + 72.2)
0
,
F2(s) =
0
2.7
s + 2.7
6.5
s + 6.5
0
G3(s) =
23.1(s + 1)
s(s + 16.3)
0
0
18.6(s + 5.9)
s(s + 84.8)
,
F3(s) =
2.1
s + 2.1
0
0
1.9
s + 1.9
G4(s) =
0
95.6(s + 2.5)
s(s + 83.3)
24.7(s + 1.2)
s(s + 99.8)
0
,
F4(s) =
0
1.7
s + 1.74
1.8
s + 1.8
0
.
Finally, a supervisory architecture determines the active
decentralized controller which should be placed in the feedback
loop. This selection is based on the values of the monitoring
signal. A schematic diagram of the overall multiple-model based
switching structure is depicted in Fig. 3.
Example 2 (Quadruple-Tank Process). The quadruple-tank process
shown in Fig. 8 is considered to illustrate the effectiveness
of the proposed design procedure. The tank consists of four
interconnected water tanks and two pumps. The input signals
are the voltages v1 and v2 applied to the two pumps and the
outputs are y1 and y2 representing the water level in tanks 1 and 2,
respectively. There are two valves that facilitate flows to the tanks.
One of the features of the linear dynamic model for the process
is the variable appropriate input–output pairing depending on
the user adjustable valve settings. This provides an interesting
challenge for linear decentralized design paradigms [5].
The control objective is the control of two lower tanks levels,
h1 and h2, using the two pumps. Using the mass balances and
Bernoulli’s law, the equations describing the plant are
dh1
dt
= −
a1
A1
2gh1 +
a3
A1
2gh3 +
γ1k1
A1
v1
dh2
dt
= −
a2
A2
2gh2 +
a4
A2
2gh4 +
γ2k2
A2
v2
7. 138 O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140
Fig. 9. Results of switching PI control for the MP setting. The plots show simulations with the nonlinear physical model.
dh3
dt
= −
a3
A3
2gh3 +
(1 − γ2)k2
A3
v2
dh4
dt
= −
a4
A4
2gh4 +
(1 − γ1)k1
A4
v1
where hi, Ai and ai for i = 1, . . . , 4 denote the level, cross-section
and outlet hole cross sections of the ith tank, respectively. Also, g
denotes the gravity acceleration. In the above equations, kivi is the
corresponding flow to the pump voltage, vi. Moreover, γ1, γ2 ∈
(0,1) indicate the division ratio of flow using the valves. And, the
measured level signals are y1 = kc h1 and y2 = kc h2, where kc is a
measurement constant.
The linearized dynamics at a given stationary operating point is
determined from the state space
dx
dt
=
−
1
T1
0
A3
A1T3
0
0 −
1
T2
0
A4
A2T4
0 0 −
1
T3
0
0 0 0 −
1
T4
x
+
γ1k1
A1
0
0
γ2k2
A2
0
(1 − γ2)k2
A3
(1 − γ1)k1
A4
0
u
y =
[
kc 0 0 0
0 kc 0 0
]
with the variables xi := hi − ho
i and ui := vi − vo
i and the time
constants are given by Ti = Ai
ai
2 ho
i
g
, i = 1, . . . , 4. At a particular
ho
i , the stationary control signal is obtained by solving the following
equations
a1
A1
2gho
1 =
γ1k1
A1
vo
1 +
(1 − γ2)k2
A1
vo
2
a2
A2
2gho
2 =
(1 − γ1)k1
A2
vo
1 +
γ2k2
A2
vo
2.
Finally, the transfer function matrix corresponding to the
stationary operating point is
M(s) =
γ1T1k1kc
A1(1 + sT1)
(1 − γ2)T1k2kc
A1(1 + sT1)(1 + sT3)
(1 − γ1)T2k1kc
A2(1 + sT2)(1 + sT4)
γ2T2k2kc
A2(1 + sT2)
.
The corresponding RGA is
Λ =
[
λ 1 − λ
1 − λ λ
]
where λ = γ1γ2
γ1+γ2−1
. If λ > 0 or 1 < γ1 +γ2 < 2 then (y1 −u1/y2 −
u2) is the appropriate input–output pair for decentralized control.
However, for 0 < γ1 + γ2 < 1, the closed-loop performance will
be better if y1 and y2 are permuted in the control structure and
the decentralized control is considered with pairings (y1, u2) and
(y2, u1).
It is also shown that the system is minimum phase (MP) for
1 < γ1 + γ2 < 2, and non-minimum phase (NMP) for 0 <
γ1 + γ2 < 1 that is inherently more difficult to control. Note that,
the aforementioned permutation, however, does not change the
location of the right half-plane zero, and experiments have shown
that the settling times are still much larger than the minimum-
phase setting [5]. The chosen operating points and the parameter
values corresponding to the MP and NMP settings are given in
Table 2.
In this section, decentralized PI control is applied to the
nonlinear process model. A decentralized PI controller as a
8. O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140 139
Fig. 10. Results of switching PI control for the NMP setting. The plots show simulations with the nonlinear physical model.
Table 2
Nominal operating conditions and parameter values of the quadruple-tank process.
Symbol State/parameters Value (MP setting) Value (NMP setting)
ho
1, ho
2, ho
3, ho
4 Nominal levels (cm) 12.4, 12.7, 1.8, 1.4 12.6, 13.0, 4.8, 4.9
vo
1, vo
2 Nominal pomp voltages (V) 3.00, 3.00 3.15, 3.15
A1, A2, A3, A4 Areas of the tanks (cm2
) 28, 32, 28, 32 28, 32, 28, 32
a1, a2, a3, a4 Areas of the drain in the tank (cm2
) 0.071, 0.057, 0.071, 0.057 0.071, 0.057, 0.071, 0.057
γ1 Ratio of flow in tank 1 to flow in tank 4 0.70 0.43
γ2 Ratio of flow in tank 2 to flow in tank 3 0.60 0.34
k1, k2 Pump constants (cm3
/Vs) 3.33, 3.35 3.14, 3.29
T1, T2, T3, T4 Time constants in the linearized model (s) 62, 90, 23, 30 63, 91, 39, 56
kc Measurement constant (V/cm) 0.50 0.50
G Gravitation constant (cm/s2
) 981 981
combination of two SISO PI controllers is considered. PI controllers
of the form
gl(s) = Kl
1 +
1
τils
, l = 1, 2
are tuned based on the linear physical model which is accurate and
agree with the response of the real process. Then, PI controllers
are incorporated into the proposed switching control structure to
deal with the variable input–output pairing of the multivariable
process.
For the MP setting, it is easy to find controller parameters
which yield good performance. The controller settings are adopted
from [5] as (K1, τi1) = (3.0, 30) and (K2, τi2) = (2.7, 40). Due to
the fact that the non-minimum phase process is normally harder
to control than the minimum phase one, it is difficult to find the
controller parameters which give good closed-loop performance
for the NMP setting. The controller parameters (K1, τi1) =
(0.94, 187.3) and (K2, τi2) = (0.99, 197.3) which are borrowed
from [25] stabilize the process and give reasonable performance.
Thus, the decentralized controllers are as follows:
G1(s) =
3.0
1 +
1
30s
0
0 2.7
1 +
1
40s
,
G2(s) =
0 0.94
1 +
1
187.3s
0.99
1 +
1
197.3s
0
.
If a diagonal decentralized controller is employed, the appro-
priate input–output pairing corresponding to NMP setting leads
to much slower responses than in the minimum-phase case. The
settling time for the step responses, which is an important char-
acteristic of the system, is approximately ten times longer for the
nonminimum-phase setting [5]. However, in the case of a switch-
ing supervisory control design, the appropriate input–output pair
is recognized by the supervisor. Figs. 9 and 10 show that the decen-
tralized switching-PI controller can easily handle the two MP and
NMP settings.
To proceed with simulation, assume that the process is working
in MP settings. In addition, the hysteresis constant h in the
switching law (6) is set to be h = 0.1. Suppose that the second
candidate controller is connected into the loop initially, that is,
σ(0) = 2. Fig. 9 depicts the closed-loop input–output trajectories.
These exhibit satisfactory closed-loop performance. The switching
signal identifies the ‘‘right’’ controllers via 1 switch. Furthermore,
we set the first controller initially, i.e., σ(0) = 1, and carry out the
simulation again for the NMP settings. Simulation results are given
in Fig. 10. The ‘‘right’’ controller corresponding to the appropriate
9. 140 O. Namaki-Shoushtari, A. Khaki-Sedigh / ISA Transactions 51 (2012) 132–140
input–output pair is identified by the supervisor and the closed
loop performance is good enough.
6. Conclusion
This paper presents the application of multivariable switching
multiple model based adaptive control for complex multivariable
plants. Large plant uncertainties lead to different input–output
pairings in multivariable plants. The proposed control structure
consists of a bank of candidate controllers and a supervisor. The
underlying design strategy is decentralized MIMO QFT. Each of
the candidate controllers is designed in order to achieve the
demanded performance in a subregion of the plant uncertainty.
The supervisor consists of a multi-estimator, a performance
signal generator and a hysteresis switching logic scheme. The
supervisor selects the active controller corresponding to the local
model which best fits the plant input–output data. Simulation
results are presented to show the effectiveness of the proposed
methodology in the face of varying control configuration in
complex multivariable plants.
References
[1] Skogestad S, Postlethwaite I. Multivariable feedback control analysis and
design. 2nd ed. John Wiley & Sons; 2005.
[2] Bristol E. On a new measure of interaction for multivariable process control.
IEEE Trans Autom Control 1966;11:133–4.
[3] Khaki-Sedigh A, Moaveni B. Control configuration selection for multivariable
plants. LNCIS, vol. 391. Berlin (Heidelberg): Springer-Verlag; 2009.
[4] Moaveni B, Khaki-Sedigh A. Reconfigurable controller design for linear
multivariable systems. Int J Model Ident Control 2007;2:138–46.
[5] Johansson KH. The quadruple-tank process: a multivariable laboratory
process with an adjustable zero. IEEE Trans Control Syst Technol 2000;8(3):
456–465.
[6] Wood RK, Berry MW. Terminal composition control of a binary distillation
column. Chem Eng Sci 1973;28:1707–17.
[7] Chen D, Seborg DE. Relative gain array analysis for uncertain process models.
AIChE J 2002;48(2):302–10.
[8] Moaveni B, Khaki-Sedigh A. Input–output pairing analysis for uncertain
multivariable processes. J Process Control 2008;18:527–32.
[9] Hespanha JP, Liberzon D, Morse AS. Overcoming the limitations of adaptive
control by means of logic-based switching. Systems Control Lett 2003;49(1):
49–65.
[10] Böling JM, Seborg DE, Hespanha JP. Multi-model adaptive control of a
simulated pH neutralization process. Control Eng Pract 2007;15:663–72.
[11] Liberzon D. Switching in systems and control. Boston: Birkhäuser; 2003.
[12] Sun Z, Ge SS. Stability theory of switched dynamical systems. London:
Springer-Verlag; 2011.
[13] Houpis CH, Rasmussen SJ, Garcia-Sanz M. Quantitative feedback theory:
fundamentals and applications. 2nd ed. Florida: A CRC Press Book, Taylor &
Francis; 2006.
[14] Garcia-Sanz M, Elso J. Beyond the linear limitations by combining switching &
QFT: application to wind turbines pitch control systems. International Journal
of Robust and Nonlinear Control 2009;19(1):40–58. [Special issue: Wind
turbines: new challenges and advanced control solutions].
[15] Namaki-Shoushtari O, Khaki Sedigh A. Design of supervisory based switching
QFT controllers for improved closed loop performance. In: Proceedings of
the 18th Iranian conference on electrical engineering. ICEE 2010. 2010.
p. 599–604.
[16] Namaki-Shoushtari O, Khaki Sedigh A. Design of decentralized supervisory
based switching QFT controller for uncertain multivariable plants. In:
Proceedings of the 48th IEEE conference on decision and control. 2009.
p. 934–9.
[17] Hespanha JP, Liberzon D, Morse AS. Bounds on the number of switchings
with scale independent hysteresis: applications to supervisory control. In:
Proceedings of the 39th IEEE conf. on decision and contr. vol. 4. 2000.
p. 3622–7.
[18] Hespanha JP. Tutorial on supervisory control. Orlando, FL: Lecture Notes for
the Workshop Control Using Logic and Switching for the 40th IEEE CDC; 2001.
[19] Morse AS. Supervisory control of families of linear set-point controllers—part
1: exact matching. IEEE Trans Autom Control 1996;41(10):1413–31.
[20] Morse AS. Control using logic-based switching. In: Isidori A, editor. Trends in
control: an European perspective. London: Springer-Verlag; 1995. p. 69–113.
[21] Su S, Anderson B, Brinsmead T. Minimal multirealization of MIMO linear
systems. IEEE Trans Autom Control 2006;51(4):690–5.
[22] Popov VM. Invariant description of linear, time-invariant controllable systems.
SIAM J Control 1972;10:252–64.
[23] Sadeghi H. State sharing in multivariable systems and its application in
switching control. MSc. thesis, K.N. Toosi University of Technology; Spring
2010.
[24] Kailath T. Linear systems. New Jersey: Prentice-Hall; 1980.
[25] Vadigepalli R, Gatzke EP, Doyle III FJ. Robust control of a multivariable
experimental four-tank system. Ind Eng Chem Res 2001;40(8):1916–27.