This document describes a model-based autotuning system that uses an artificial neural network (ANN) and relay feedback test. The system estimates process parameters like gain, ultimate gain, ultimate frequency, and apparent deadtime from relay feedback test data. It then classifies the process dynamics and tunes PI/PID controllers based on either a first-order plus deadtime or second-order plus deadtime process model. The tuning rules are derived from these models to provide superior control performance compared to Ziegler-Nichols tuning.
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.
This document describes a new design method for fractional-order PID (FOPID) controllers. It introduces a biquadratic approximation of fractional-order differential operators to create a new structure for finite-order FOPID controllers with fewer parameters to tune than existing designs. The proposed FOPID controller design uses the biquadratic approximation within a modular design approach, cascading multiple modules to improve robustness. A numerical example is used to verify the design method.
Design of Fractional Order PID controller using Soft computing methods for a ...IOSR Journals
This document describes a study that designs a fractional order PID (FOPID) controller using soft computing methods for a buck-boost DC-DC power converter. A FOPID controller is proposed to improve the dynamic response of the converter compared to a conventional PID controller. Particle swarm optimization and cuckoo search algorithms are used to tune the parameters of the FOPID controller (KP, Ki, Kd, λ, μ) to regulate the output voltage. Simulation results show that the FOPID controller designed with both algorithms achieves faster response times, lower overshoot, and better settling performance compared to a PID controller.
The document discusses fractional order PID tuning and control. It introduces fractional order systems and controllers (FOPID), and describes some of their advantages over traditional PID controllers, including better modeling of dynamic systems and more robust control design. It then discusses several FOPID tuning methods, focusing on the Taylor series expansion method which matches terms between the actual and desired closed-loop transfer functions to increase tracking accuracy.
Numerical Optimization of Fractional Order PID Controller inventionjournals
: The fractional order PID controller is the generalization of classical PID controller, many Researchers interest in tuning FOPID controller here we use the Pareto Optimum technique to estimate the controller parameter and compare our result with the classical model and with other Researchers result .we used both mathematica package and matlab for tuning and simulation
Comparison Analysis of Model Predictive Controller with Classical PID Control...ijeei-iaes
pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC) is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT) model controlled by Proportional Integral Derivative (PID) and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.
This document describes a new method for designing fractional-order proportional-integral-derivative (FOPID) controllers. It introduces approximating fractional-order differential operators using a biquadratic structure, which allows designing finite-order FOPID controllers with fewer parameters than existing designs. A systematic procedure is presented to design FOPID controllers to achieve desired phase and gain margins of controlled systems. The viability of the design method is verified with a numerical example.
Use of feedback control to improve hil based ecu system function testingYixin Chen
This document proposes using feedback control to improve hardware-in-the-loop (HIL) based ECU system function testing. It introduces a method that uses feedback from either directly connecting an output signal back to the HIL simulator (hardware feedback) or accessing an internal ECU variable through a communication protocol (software feedback). This feedback is used in a PID control loop to dynamically adjust inputs to drive the output or variable to a target value. The document presents a case study using throttle position control to demonstrate this method. It evaluates the hardware and software feedback approaches and concludes that feedback control enhances HIL-based testing capabilities when transfer functions are unclear.
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.
This document describes a new design method for fractional-order PID (FOPID) controllers. It introduces a biquadratic approximation of fractional-order differential operators to create a new structure for finite-order FOPID controllers with fewer parameters to tune than existing designs. The proposed FOPID controller design uses the biquadratic approximation within a modular design approach, cascading multiple modules to improve robustness. A numerical example is used to verify the design method.
Design of Fractional Order PID controller using Soft computing methods for a ...IOSR Journals
This document describes a study that designs a fractional order PID (FOPID) controller using soft computing methods for a buck-boost DC-DC power converter. A FOPID controller is proposed to improve the dynamic response of the converter compared to a conventional PID controller. Particle swarm optimization and cuckoo search algorithms are used to tune the parameters of the FOPID controller (KP, Ki, Kd, λ, μ) to regulate the output voltage. Simulation results show that the FOPID controller designed with both algorithms achieves faster response times, lower overshoot, and better settling performance compared to a PID controller.
The document discusses fractional order PID tuning and control. It introduces fractional order systems and controllers (FOPID), and describes some of their advantages over traditional PID controllers, including better modeling of dynamic systems and more robust control design. It then discusses several FOPID tuning methods, focusing on the Taylor series expansion method which matches terms between the actual and desired closed-loop transfer functions to increase tracking accuracy.
Numerical Optimization of Fractional Order PID Controller inventionjournals
: The fractional order PID controller is the generalization of classical PID controller, many Researchers interest in tuning FOPID controller here we use the Pareto Optimum technique to estimate the controller parameter and compare our result with the classical model and with other Researchers result .we used both mathematica package and matlab for tuning and simulation
Comparison Analysis of Model Predictive Controller with Classical PID Control...ijeei-iaes
pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC) is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT) model controlled by Proportional Integral Derivative (PID) and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.
This document describes a new method for designing fractional-order proportional-integral-derivative (FOPID) controllers. It introduces approximating fractional-order differential operators using a biquadratic structure, which allows designing finite-order FOPID controllers with fewer parameters than existing designs. A systematic procedure is presented to design FOPID controllers to achieve desired phase and gain margins of controlled systems. The viability of the design method is verified with a numerical example.
Use of feedback control to improve hil based ecu system function testingYixin Chen
This document proposes using feedback control to improve hardware-in-the-loop (HIL) based ECU system function testing. It introduces a method that uses feedback from either directly connecting an output signal back to the HIL simulator (hardware feedback) or accessing an internal ECU variable through a communication protocol (software feedback). This feedback is used in a PID control loop to dynamically adjust inputs to drive the output or variable to a target value. The document presents a case study using throttle position control to demonstrate this method. It evaluates the hardware and software feedback approaches and concludes that feedback control enhances HIL-based testing capabilities when transfer functions are unclear.
FRACTIONAL ORDER PID CONTROLLER TUNING BASED ON IMC IJITCA Journal
In this work, a class of fractional order controller (FOPID) is tuned based on internal model control
(IMC). This tuning rule has been obtained without any approximation of time delay. Moreover to show
usefulness of fractional order controller in comparison with classical integer order controllers, an
industrial PID controller tuned in a similar way, is compared with FOPID and then robust stability of both
controllers is investigated. Robust stability analysis has been done to find maximum delayed time
uncertainty interval which results in a stable closed loop control system. For a typical system, robust
stability has been done to find maximum time constant uncertainty interval of system. Two clarify the
proposed control system design procedure, three examples have been given.
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.
Mathematical Modeling and Fuzzy Adaptive PID Control of Erection MechanismTELKOMNIKA JOURNAL
This paper describes an application of fuzzy adaptive PID controller to erection mechanism.
Mathematical model of erection mechanism was derived. Erection mechanism is driven by electrohydraulic
actuator system which is difficult to control due to its nonlinearity and complexity. Therefore fuzzy
adaptive PID controller was applied to control the system. Simulation was performed in Simulink software
and experiment was accomplished on laboratory equipment. Simulation and experiment results of erection
angle controlled by fuzzy logic, PID and fuzzy adaptive PID controllers were respectively obtained. The
results show that fuzzy adaptive PID controller can effectively achieve the best performance for erection
mechanism in comparison with fuzzy logic and PID controllers.
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.
Tuning of PID controllers for integrating systems using direct synthesis methodISA Interchange
A PID controller is designed for various forms of integrating systems with time delay using direct synthesis method. The method is based on comparing the characteristic equation of the integrating system and PID controller with a filter with the desired characteristic equation. The desired characteristic equation comprises of multiple poles which are placed at the same desired location. The tuning parameter is adjusted so as to achieve the desired robustness. Tuning rules in terms of process parameters are given for various forms of integrating systems. The tuning parameter can be selected for the desired robustness by specifying Ms value. The proposed controller design method is applied to various transfer function models and to the nonlinear model equations of jacketed CSTR to show its effectiveness and applicability.
Design of PI controllers for achieving time and frequency domain specificatio...ISA Interchange
This document presents a new method for designing PI controllers that achieve both desired frequency domain and time domain specifications simultaneously. The method involves two main steps:
1. Computing the global and local stability regions of PI controller parameters that stabilize the system using a boundary locus approach.
2. Using the coefficient diagram method to design PI controllers within the local stability region such that the closed-loop system meets specifications for time domain measures like overshoot and settling time.
This provides a graphical tool called a frequency and time domain performances map that shows which PI controller parameters satisfy both the frequency and time domain performance criteria. Examples are given to demonstrate the benefits of the proposed design method.
This document presents a comparative study of monotonic and non-monotonic phase linear time-invariant (LTI) systems using an improved analytical PID controller design. It discusses using gain crossover frequency and phase margin specifications to design controllers that ensure minimum phase margin inside the desired bandwidth. For the comparative study, it uses bode stability criterion, Nyquist stability criterion, and unit step response. It presents a case study comparing the design of controllers for a buck converter system, which exhibits a non-monotonic phase response, using both monotonic and non-monotonic design techniques. The results show that treating the non-monotonic system as monotonic leads to an overvalued proportional gain and undervalued derivative gain in the PID controller.
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.
This document summarizes a study comparing three control methods - PID, IMC, and IMC-PID - for controlling a first-order motor-tachometer system. The key findings are:
1) IMC performs better than PID when near system limitations, as PID can exhibit reset windup causing poor control. IMC avoids this issue.
2) Both IMC and IMC-PID effectively control the system under normal operation. However, IMC has less noise than IMC-PID.
3) When a large disturbance occurs, IMC returns to the setpoint faster than IMC-PID, which overshoots due to integral windup.
Modern control systems incorporate feedback to achieve desired purposes. Early examples of control systems provided ideas still used today. Control engineering now improves manufacturing, energy efficiency, transportation and more.
New controllers efficient model based design methodAlexander Decker
This document proposes new methods for designing P, PI, PD, and PID controllers based on selecting the controller gains based on the plant's parameters. The goal is to achieve acceptable stability and medium fast response. Expressions are proposed for calculating the controller gains for first-order, second-order, and time-delay systems based on the plant's time constant, damping ratio, and natural frequency. The proposed controller design methods are tested on first, second, and first-order systems with time delay using MATLAB/Simulink. The results show the methods can achieve acceptable stability and medium fast response with minimum steady state error by selecting a single tuning parameter.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
Model predictive control (MPC) is an advanced contr
ol algorithm that has been very successful in the
control industries due to its capability of handlin
g multi input multi output (MIMO) systems with phys
ical
constraints. In MPC, the control action are obtaine
d by solving a constrained optimization problem at
every sample interval to minimize the difference be
tween the predicted outputs and the reference value
through the using of minimum control energy and sat
isfying the constraints of the physical system.
Quadratic programing (QP) problem is solved using Q
PKWIK method which improves the active set
method. The system architecture and design for the
implementation of online MPC on the FPGA is taken
into consideration in this paper to control a DC mo
tor. This implementation is completed using Spartan
6
Nexys3 FPGA chip using simulation environment (EDK
tool) and the comparison between MPC and PID
controller is also established.
Robust pole placement using firefly algorithmIJECEIAES
In this paper, the new automatic tool that is based on the firefly algorithm whose purpose is optimization of pole location in the control of state feedback has been presented. The aim is satisfying specifications of performance like settling and rise time, steady state as well as overshoot error. Utilization of Firefly algorithm has demonstrated the benefits of controllers based on this kind of time domain over controllers based on the frequency domain like Proportional-Integral Derivative (PID). The presented method is more particular for the multi-input multi-output (MIMO) systems that have substantial state numbers. The simulation results indicated that the proposed method had superior performance in providing solution to the problems that involved stabilization of helicopter under the Rationalized Model of helicopter/ Moreover, it demonstrates the Firefly algorithm effectiveness with regards to, the state observer design and feedback controller and auto-tuning.
An adaptive PID like controller using mix locally recurrent neural network fo...ISA Interchange
Being complex, non-linear and coupled system, the robotic manipulator cannot be effectively controlled using classical proportional integral derivative (PID) controller. To enhance the effectiveness of the conventional PID controller for the nonlinear and uncertain systems, gains of the PID controller should be conservatively tuned and should adapt to the process parameter variations. In this work, a mix locally recurrent neural network (MLRNN) architecture is investigated to mimic a conventional PID controller which consists of at most three hidden nodes which act as proportional, integral and derivative node. The gains of the mix locally recurrent neural network based PID (MLRNNPID) controller scheme are initi- alized with a newly developed cuckoo search algorithm (CSA) based optimization method rather than assuming randomly. A sequential learning based least square algorithm is then investigated for the on- line adaptation of the gains of MLRNNPID controller. The performance of the proposed controller scheme is tested against the plant parameters uncertainties and external disturbances for both links of the two link robotic manipulator with variable payload (TL-RMWVP). The stability of the proposed controller is analyzed using Lyapunov stability criteria. A performance comparison is carried out among MLRNNPID controller, CSA optimized NNPID (OPTNNPID) controller and CSA optimized conventional PID (OPTPID) controller in order to establish the effectiveness of the MLRNNPID controller.
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.
Dynamic Matrix Control (DMC) on jacket tank heater - Rishikesh BagweRishikesh Bagwe
The Dynamic Matrix Control (DMC) method of Model Predictive Control was simulated in MATLAB on Jacketed Tank Heater. The characteristics of the liquid being controlled are height and temperature
This document is the preface to volume 1 of the revised and enlarged 1912 edition of A Dictionary of Applied Chemistry. It discusses the extensive advances in chemistry and its applications to industry that have occurred in the 22 years since the original edition. As a result, the dictionary has been greatly expanded and most articles have been revised or rewritten. Contributors include eminent experts from the UK, US, Germany and elsewhere. The editor acknowledges assistance from researchers at the Imperial College of Science and Technology for their help revising and compiling articles.
This document presents a method for automatically tuning PID controllers using particle swarm optimization (PSO) algorithm. It describes PID controllers and common tuning methods like Ziegler-Nichols. It then provides an overview of PSO algorithm and how it can be applied to optimize PID parameters to minimize a performance index for a DC motor model. Simulation results show the PSO-tuned PID controller provides improved rise time, settling time and overshoot compared to Ziegler-Nichols tuning.
FRACTIONAL ORDER PID CONTROLLER TUNING BASED ON IMC IJITCA Journal
In this work, a class of fractional order controller (FOPID) is tuned based on internal model control
(IMC). This tuning rule has been obtained without any approximation of time delay. Moreover to show
usefulness of fractional order controller in comparison with classical integer order controllers, an
industrial PID controller tuned in a similar way, is compared with FOPID and then robust stability of both
controllers is investigated. Robust stability analysis has been done to find maximum delayed time
uncertainty interval which results in a stable closed loop control system. For a typical system, robust
stability has been done to find maximum time constant uncertainty interval of system. Two clarify the
proposed control system design procedure, three examples have been given.
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.
Mathematical Modeling and Fuzzy Adaptive PID Control of Erection MechanismTELKOMNIKA JOURNAL
This paper describes an application of fuzzy adaptive PID controller to erection mechanism.
Mathematical model of erection mechanism was derived. Erection mechanism is driven by electrohydraulic
actuator system which is difficult to control due to its nonlinearity and complexity. Therefore fuzzy
adaptive PID controller was applied to control the system. Simulation was performed in Simulink software
and experiment was accomplished on laboratory equipment. Simulation and experiment results of erection
angle controlled by fuzzy logic, PID and fuzzy adaptive PID controllers were respectively obtained. The
results show that fuzzy adaptive PID controller can effectively achieve the best performance for erection
mechanism in comparison with fuzzy logic and PID controllers.
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.
Tuning of PID controllers for integrating systems using direct synthesis methodISA Interchange
A PID controller is designed for various forms of integrating systems with time delay using direct synthesis method. The method is based on comparing the characteristic equation of the integrating system and PID controller with a filter with the desired characteristic equation. The desired characteristic equation comprises of multiple poles which are placed at the same desired location. The tuning parameter is adjusted so as to achieve the desired robustness. Tuning rules in terms of process parameters are given for various forms of integrating systems. The tuning parameter can be selected for the desired robustness by specifying Ms value. The proposed controller design method is applied to various transfer function models and to the nonlinear model equations of jacketed CSTR to show its effectiveness and applicability.
Design of PI controllers for achieving time and frequency domain specificatio...ISA Interchange
This document presents a new method for designing PI controllers that achieve both desired frequency domain and time domain specifications simultaneously. The method involves two main steps:
1. Computing the global and local stability regions of PI controller parameters that stabilize the system using a boundary locus approach.
2. Using the coefficient diagram method to design PI controllers within the local stability region such that the closed-loop system meets specifications for time domain measures like overshoot and settling time.
This provides a graphical tool called a frequency and time domain performances map that shows which PI controller parameters satisfy both the frequency and time domain performance criteria. Examples are given to demonstrate the benefits of the proposed design method.
This document presents a comparative study of monotonic and non-monotonic phase linear time-invariant (LTI) systems using an improved analytical PID controller design. It discusses using gain crossover frequency and phase margin specifications to design controllers that ensure minimum phase margin inside the desired bandwidth. For the comparative study, it uses bode stability criterion, Nyquist stability criterion, and unit step response. It presents a case study comparing the design of controllers for a buck converter system, which exhibits a non-monotonic phase response, using both monotonic and non-monotonic design techniques. The results show that treating the non-monotonic system as monotonic leads to an overvalued proportional gain and undervalued derivative gain in the PID controller.
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.
This document summarizes a study comparing three control methods - PID, IMC, and IMC-PID - for controlling a first-order motor-tachometer system. The key findings are:
1) IMC performs better than PID when near system limitations, as PID can exhibit reset windup causing poor control. IMC avoids this issue.
2) Both IMC and IMC-PID effectively control the system under normal operation. However, IMC has less noise than IMC-PID.
3) When a large disturbance occurs, IMC returns to the setpoint faster than IMC-PID, which overshoots due to integral windup.
Modern control systems incorporate feedback to achieve desired purposes. Early examples of control systems provided ideas still used today. Control engineering now improves manufacturing, energy efficiency, transportation and more.
New controllers efficient model based design methodAlexander Decker
This document proposes new methods for designing P, PI, PD, and PID controllers based on selecting the controller gains based on the plant's parameters. The goal is to achieve acceptable stability and medium fast response. Expressions are proposed for calculating the controller gains for first-order, second-order, and time-delay systems based on the plant's time constant, damping ratio, and natural frequency. The proposed controller design methods are tested on first, second, and first-order systems with time delay using MATLAB/Simulink. The results show the methods can achieve acceptable stability and medium fast response with minimum steady state error by selecting a single tuning parameter.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
Model predictive control (MPC) is an advanced contr
ol algorithm that has been very successful in the
control industries due to its capability of handlin
g multi input multi output (MIMO) systems with phys
ical
constraints. In MPC, the control action are obtaine
d by solving a constrained optimization problem at
every sample interval to minimize the difference be
tween the predicted outputs and the reference value
through the using of minimum control energy and sat
isfying the constraints of the physical system.
Quadratic programing (QP) problem is solved using Q
PKWIK method which improves the active set
method. The system architecture and design for the
implementation of online MPC on the FPGA is taken
into consideration in this paper to control a DC mo
tor. This implementation is completed using Spartan
6
Nexys3 FPGA chip using simulation environment (EDK
tool) and the comparison between MPC and PID
controller is also established.
Robust pole placement using firefly algorithmIJECEIAES
In this paper, the new automatic tool that is based on the firefly algorithm whose purpose is optimization of pole location in the control of state feedback has been presented. The aim is satisfying specifications of performance like settling and rise time, steady state as well as overshoot error. Utilization of Firefly algorithm has demonstrated the benefits of controllers based on this kind of time domain over controllers based on the frequency domain like Proportional-Integral Derivative (PID). The presented method is more particular for the multi-input multi-output (MIMO) systems that have substantial state numbers. The simulation results indicated that the proposed method had superior performance in providing solution to the problems that involved stabilization of helicopter under the Rationalized Model of helicopter/ Moreover, it demonstrates the Firefly algorithm effectiveness with regards to, the state observer design and feedback controller and auto-tuning.
An adaptive PID like controller using mix locally recurrent neural network fo...ISA Interchange
Being complex, non-linear and coupled system, the robotic manipulator cannot be effectively controlled using classical proportional integral derivative (PID) controller. To enhance the effectiveness of the conventional PID controller for the nonlinear and uncertain systems, gains of the PID controller should be conservatively tuned and should adapt to the process parameter variations. In this work, a mix locally recurrent neural network (MLRNN) architecture is investigated to mimic a conventional PID controller which consists of at most three hidden nodes which act as proportional, integral and derivative node. The gains of the mix locally recurrent neural network based PID (MLRNNPID) controller scheme are initi- alized with a newly developed cuckoo search algorithm (CSA) based optimization method rather than assuming randomly. A sequential learning based least square algorithm is then investigated for the on- line adaptation of the gains of MLRNNPID controller. The performance of the proposed controller scheme is tested against the plant parameters uncertainties and external disturbances for both links of the two link robotic manipulator with variable payload (TL-RMWVP). The stability of the proposed controller is analyzed using Lyapunov stability criteria. A performance comparison is carried out among MLRNNPID controller, CSA optimized NNPID (OPTNNPID) controller and CSA optimized conventional PID (OPTPID) controller in order to establish the effectiveness of the MLRNNPID controller.
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.
Dynamic Matrix Control (DMC) on jacket tank heater - Rishikesh BagweRishikesh Bagwe
The Dynamic Matrix Control (DMC) method of Model Predictive Control was simulated in MATLAB on Jacketed Tank Heater. The characteristics of the liquid being controlled are height and temperature
This document is the preface to volume 1 of the revised and enlarged 1912 edition of A Dictionary of Applied Chemistry. It discusses the extensive advances in chemistry and its applications to industry that have occurred in the 22 years since the original edition. As a result, the dictionary has been greatly expanded and most articles have been revised or rewritten. Contributors include eminent experts from the UK, US, Germany and elsewhere. The editor acknowledges assistance from researchers at the Imperial College of Science and Technology for their help revising and compiling articles.
This document presents a method for automatically tuning PID controllers using particle swarm optimization (PSO) algorithm. It describes PID controllers and common tuning methods like Ziegler-Nichols. It then provides an overview of PSO algorithm and how it can be applied to optimize PID parameters to minimize a performance index for a DC motor model. Simulation results show the PSO-tuned PID controller provides improved rise time, settling time and overshoot compared to Ziegler-Nichols tuning.
Este documento presenta información sobre el libro 400 pequeñas dosis de ciencia publicado por la Coordinación de la Investigación Científica de la UNAM en 2007. Incluye los nombres de los colaboradores, la coordinación ejecutiva y el diseño del libro, así como detalles sobre la publicación como la fecha, editorial y ISBN. Además, presenta extractos de algunas de las pequeñas dosis de ciencia incluidas en el libro sobre temas de aves en peligro, la abeja reina, la vejez y la ceguera
El curso cubre temas relacionados a líneas de transmisión y estaciones de 500 kV, incluyendo su planificación, aspectos ambientales, diseño y mantenimiento. Se analizan parámetros de diseño para líneas como su configuración, cantidad de conductores y distancias entre fases. También se discuten criterios para la inspección y mantenimiento de líneas, y el diseño de conductores para mitigar vibraciones eólicas mediante el uso de espaciadores.
This document discusses a study on the effectiveness of performance management systems (PMS) as a tool for people alignment and development at Bank of Ceylon. The researchers interviewed a personal manager at a Kandy branch to understand how PMS works. They found that PMS is effective at aligning individual goals with organizational objectives through monthly reviews. However, areas for improvement include making the manager review form less lengthy and subjective, adding self-appraisals, and prioritizing performance over seniority for promotions to better motivate employees. The researchers recommend making PMS a more transparent process that develops individuals and the organization.
Los plásticos, el ADN, el ARN y las proteínas son moléculas grandes formadas por la unión de muchas unidades más pequeñas llamadas monómeros. El ADN almacena y transmite la información genética, el ARN participa en la síntesis de proteínas y las proteínas llevan a cabo funciones estructurales y metabólicas en los seres vivos.
This document is a report on an exercise using a microcontroller. It includes a table with the pin names and numbers for an ATmega328P microcontroller. The microcontroller is connected to an LED on pin 22 through resistor R2, and receives power from a 5V supply through a 0.1uF capacitor C1 connected from the power to ground.
El documento resume los eventos trágicos de marzo de 2013 en Ecuador cuando dos ancianos Waorani fueron asesinados por un grupo de indígenas Tagaeri-Taromenani aislados y cómo las instituciones estatales respondieron. Luego, familiares Waorani ingresaron a la selva para vengar las muertes, matando e secuestrando a dos niñas Tagaeri-Taromenani. El documento también analiza la debilidad institucional del Estado ecuatoriano y la falta de coordinación entre los diferentes niveles de gobierno para prote
Los receptores sensitivos captan información del medio interno y externo mediante estímulos. Existen receptores internos (enterceptores) que detectan el estado fisiológico del cuerpo y receptores externos que constituyen los órganos de los sentidos como la vista, el oído, el tacto, el gusto y el olfato. La información captada por los receptores se transmite al cerebro donde se elabora una respuesta consciente.
This document discusses different methods for designing discrete equivalents of continuous transfer functions for use in digital filters and control systems. It presents three main approaches: 1) numerical integration using rectangular, backward, and trapezoid (Tustin's method) rules to map the continuous transfer function to a discrete one; 2) pole-zero mapping to understand how integration rules map the stable region of the s-plane to the z-plane; 3) prewarping the continuous transfer function before applying Tustin's method in order to minimize frequency distortion caused by the mapping. The performance of these methods is demonstrated through an example of designing discrete equivalents of a Butterworth filter.
Este documento es el texto de química para el cuarto año de educación media de Chile. Presenta información sobre temas de química como la composición y aplicación de polímeros naturales y sintéticos, la radiactividad en el contexto de la tecnología nuclear y los procesos productivos vinculados a la industria química. El texto fue escrito por Silvina Iriberri de Díaz y Romina Martínez Orellana y publicado por Editorial Santillana para el Ministerio de Educación de Chile en 2011.
This document summarizes a research project on process identification using relay feedback tests. The project aims to identify low-order models like FOPDT and SOPDT from relay feedback data to enable performance assessment and controller tuning. A new identification method is proposed that uses neural networks to estimate the apparent deadtime from steady-state cycles. This deadtime and other parameters allow classification of the process model and parameter estimation for assessment and auto-tuning.
This document provides an overview of the textbook "Environmental Soil and Water Chemistry: Principles and Applications" by V.P. Evangelou. The textbook covers principles of water chemistry, solution-mineral chemistry, soil minerals and surface properties, sorption and exchange reactions, redox chemistry and kinetics, soil dynamics related to organic matter and nutrients, colloids and transport processes in soils, salt-affected soils and brackish waters, acid drainage prevention technologies, and water quality and treatment technologies. The textbook is intended to provide students with the fundamental chemical principles needed to understand environmental processes in soil and water systems.
Global warming; Sri-Lankas contribution and our own demiseKushan Samararatne
The document discusses greenhouse gases and global warming. It notes that greenhouse gases like carbon dioxide and methane absorb infrared radiation, contributing to the greenhouse effect and rising global temperatures. It provides data showing that Sri Lanka's CO2 emissions have risen significantly over time and are primarily from electricity production and transportation. It also outlines various impacts of climate change that Sri Lanka may face like sea level rise, more extreme weather, and effects on agriculture, livestock, and human health.
Closed-loop step response for tuning PID fractional-order filter controllersISA Interchange
Analytical methods are usually applied for tuning fractional controllers. The present paper proposes an empirical method for tuning a new type of fractional controller known as PID-Fractional-Order-Filter (FOF-PID). Indeed, the setpoint overshoot method, initially introduced by Shamsuzzoha and Skogestad, has been adapted for tuning FOF-PID controller. Based on simulations for a range of first order with time delay processes, correlations have been derived to obtain PID-FOF controller parameters similar to those obtained by the Internal Model Control (IMC) tuning rule. The setpoint overshoot method requires only one closed-loop step response experiment using a proportional controller (P-controller). To highlight the potential of this method, simulation results have been compared with those obtained with the IMC method as well as other pertinent techniques. Various case studies have also been considered. The comparison has revealed that the proposed tuning method performs as good as the IMC. Moreover, it might offer a number of advantages over the IMC tuning rule. For instance, the parameters of the frac- tional controller are directly obtained from the setpoint closed-loop response data without the need of any model of the plant to be controlled.
This document presents a new control structure using a PID controller for load frequency control of power systems. The control structure places the PID controller in the feedback loop to improve disturbance rejection and robustness against plant parameter uncertainties. A relay feedback method is used to identify lower order transfer function models with time delay from typically higher order power system models. The PID controller parameters are then tuned using Laurent series expansion of the closed loop transfer function to provide improved performance for disturbance rejection while maintaining robustness. Simulation results on single-area and multi-area power system models demonstrate the effectiveness of the proposed control structure and PID controller design method.
Disturbance Rejection with a Highly Oscillating Second-Order Process, Part I...Scientific Review SR
This research paper aims at investigating disturbance rejection associated with a highly oscillating
second-order process. The PD-PI controller having three parameters are tuned to provide efficient rejection of a
step input disturbance input. Controller tuning based on using MATLAB control and optimization toolboxes.
Using the suggested tuning technique, it is possible to reduce the maximum time response of the closed loop
control system to as low as 0.0095 and obtain time response to the disturbance input having zero settling time.
The effect of the proportional gain of the PD-PI controller on the control system dynamics is investigated for a
gain ≤ 100. The performance of the control system during disturbance rejection using the PD -PI controller is
compared with that using a second-order compensator. The PD-PI controller is superior in dealing with the
disturbance rejection associated with the highly oscillating second-order process
This document compares the performance of PID and FOPID controllers for automatic voltage regulation (AVR) systems. It presents models for the components of an AVR system and describes integer and fractional order PID controllers. Classical tuning methods like Ziegler-Nichols and Cohen-Coon are discussed for PID tuning. Ziegler-Nichols type rules are presented for FOPID tuning. Simulation results show that a FOPID controller tuned by Ziegler-Nichols methods provides better performance than PID controllers tuned by Ziegler-Nichols or Cohen-Coon, with less overshoot, faster settling time, and reduced rise time.
Speed control of dc motor using relay feedback tuned piAlexander Decker
This document discusses speed control of a DC motor using different controller types, including a relay feedback tuned PI controller, fuzzy PI controller (FPIC), and self-tuned fuzzy PI controller (STFPIC). The FPIC and STFPIC are developed using fuzzy logic to overcome limitations of conventional PID controllers for nonlinear systems without an accurate mathematical model. An experimental setup is used to test the controllers' performance on a DC motor. Results show the model-independent STFPIC and FPIC controllers improve speed control performance compared to the relay-tuned PI controller.
Design of a new PID controller using predictive functional control optimizati...ISA Interchange
An improved proportional integral derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers.
COMPARATIVE ANALYSIS OF CONVENTIONAL PID CONTROLLER AND FUZZY CONTROLLER WIT...IJITCA Journal
All the real systems exhibits non-linear nature,conventional controllers are not always able to provide good and accurate results. Fuzzy Logic Control is used to obtain better response. A model for simulation is designed and all the assumptions are made before the development of the model. An attempt has been made to analyze the efficiency of a fuzzy controller over a conventional PID controller for a three tank level control system using fuzzification & defuzzification methods and their responses are compared. Analysis is done through computer simulation using Matlab/Simulink toolbox. This study shows that the application of Fuzzy Logic Controller (FLC) gives the best response with triangular membership function and centroid defuzzification method.
EHR ATTRIBUTE-BASED ACCESS CONTROL (ABAC) FOR FOG COMPUTING ENVIRONMENTcsandit
Liquid level tanks are employed in many industrial and chemical areas. Their level must be keep
a defined point or between maximum-minimum points depending on changing of inlet and outlet
liquid quantities. In order to overcome the problem, many level control methods have been
developed. In the paper, it was aimed that obtain a mathematical model of an installed liquid
level tank system. Then, the mathematical model was derived from the installed system
depending on the sizes of the liquid level tank. According to some proportional-integralderivative
(PID) parameters, the model was simulated by using MATLAB/Simulink program.
After that, data of the liquid level tank were taken into a computer by employing data
acquisition cards (DAQs). Lastly, the computer-controlled liquid level control was successfully
practiced through a written computer program embedded into a PID algorithm used the PID
parameters obtained from the simulations into Advantech VisiDAQ software
Hybrid Stochastic Search Technique based Suboptimal AGC Regulator Design for ...Dr. Omveer Singh
This document proposes a hybrid genetic algorithm-simulated annealing (GASA) technique for designing suboptimal automatic generation control (AGC) regulators for a two-area power system model. GASA is applied to determine the constrained feedback gains of a PI regulator using available state variables as outputs. Simulation results show the proposed GASA regulator provides better dynamic performance than suboptimal PI regulators, with lower overshoots and faster settling times in response to load perturbations. The proposed approach provides an effective yet simple suboptimal AGC solution that does not require full state information.
Ascc04 334 Comparative Study of Unstable Process ControlF15TV
This document compares several existing control methods for unstable time-delayed processes. It summarizes 6 control methods (A through F) and evaluates their performance based on simulations of processes with small, medium, and large normalized time delays. For small delays, Methods E and F showed excellent setpoint tracking and disturbance rejection. For medium delays, Methods G, E, and F performed best. For large delays, only Methods E and F were applicable, with Method E showing slightly better setpoint tracking and Method F better disturbance rejection. Based on overall performance, robustness, and applicability, the document ranks Method F as the best existing control method.
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.
IRJET- Design and Analysis of Fuzzy and GA-PID Controllers for Optimized Perf...IRJET Journal
This document describes research into using different controller types, including fuzzy logic controllers and genetic algorithm optimized PID controllers, to control a STATCOM device for improved reactive power compensation performance. A STATCOM is a shunt Flexible AC Transmission System device that can help solve power quality issues. Conventionally, PID controllers are used but require trial and error to tune parameters. The document models a STATCOM system and explores using fuzzy logic control or genetic algorithms to automatically determine optimal PID parameters to achieve faster response compared to conventional PID control. Simulation results in MATLAB show that both fuzzy logic control and genetic algorithm optimized PID control improve the STATCOM current control response compared to manually tuned PID controllers.
Optimization of Fuzzy Logic controller for Luo Converter using Genetic Algor...IRJET Journal
This document summarizes research on optimizing a fuzzy logic controller for a Luo converter using a genetic algorithm. A fuzzy logic controller was designed for the Luo converter but its parameters were determined through trial and error. The document proposes using a genetic algorithm to optimize the fuzzy logic controller's rules, membership functions, and scaling gains in order to improve the controller's performance for the Luo converter. Simulation results showed that the genetic algorithm-optimized fuzzy logic controller provided faster response, better transient performance, and more robustness to variations compared to the original fuzzy logic controller.
PRACTICAL IMPLEMENTION OF GAOPF ON INDIAN 220KV TRANSMISSION SYSTEMecij
This paper presents the practical implementation of developed genetic algorithm based optimal power flow algorithms. These algorithms are tested on IEEE30 bus system and the results were presented in the paper [8]. The same algorithms now tested on 220KV Washi zone Indian power transmission system . The GAOPF with fixed penalty and Fuzzy based variable penalty tested on 220KV transmission system consists of 52 bus and 88lines. The fuel costs ,computational time and the system condition were studied and the results are presented in this paper .Also the available load transfer capability of the 220KV system for congestion management is also presented
Simulation analysis of Series Cascade control Structure and anti-reset windup...IOSR Journals
This document presents a simulation analysis of series cascade control structure and anti-reset windup technique for a jacketed continuous stirred tank reactor (CSTR). It discusses modeling and linearization of a CSTR process. It then analyzes series cascade control structure and designs PID controllers using auto-tuning. Next, it explains an anti-reset windup protection technique to address issues like overshoot and windup. Simulation results showing step responses indicate that responses with anti-windup have less overshoot and shorter settling time compared to the conventional cascade control system. In conclusion, the anti-reset windup technique improves closed-loop performance for the CSTR process.
Comparison of Tuning Methods of PID Controllers for Non-Linear Systempaperpublications3
Abstract: Modern days have seen vast developments in the field of controller’s .There are various controllers developed these days with various different specifications. But the only drawback is that, there is no fixed method for the tuning of these controllers, which is necessary for controlling of the system based on the variation of the input or for the changes in the system. In order to overcome this drawback, in this paper we have compared various tuning methods of PID controller for non-linear system. As a non-linear system we have taken the dc motor as a system. For the particular DC motor controller transfer function has been determined and control parameters such as Proportional Gain, Integral Time and Derivative time are identified. They are numerous methods of developing a Proportional Integral and Derivative (PID) Controller, amongst them some methods are adopted in this paper and Comparisons of Time Domain specifications of those controllers has been carried out.
The document provides a literature review on PM brushless motors, PID controllers, and PID tuning methods. It discusses how PM brushless motors have advantages over other motor types due to their high efficiency, power density, and reliability. It then describes how PID controllers are widely used in motion control despite other advanced control techniques due to their robustness and ease of implementation. Finally, it reviews traditional PID tuning methods like Ziegler-Nichols and relay feedback and discusses how these methods identify critical process parameters to calculate PID gains.
Design and Control of a Hydraulic Servo System and Simulation AnalysisIJMREMJournal
This paper describes the system analysis, modeling and simulation of a Hydraulic Servo System (HSS) for
hydraulic mini press machine. Comparisons among linear output feed back PID control, Fuzzy control and
Hybrid of PID and Fuzzy control are presented. Application of hybrid controller to a nonlinear is investigated
by both position and velocity of the hydraulic servo system. The experiment is based on an 8 bit PIC
16F877 microcontroller, and the simulation is based on MATLAB Simulink. Simulation and hardware
experimental results show that the hybrid controller gave the best performance as it has the smallest overshoot,
oscillation, and setting time.
Design of Multiloop Controller for Three Tank Process Using CDM Techniques ijsc
In this study the controller for three tank multi loop system is designed using coefficient Diagram method. Coefficient Diagram Method is one of the polynomial methods in control design. The controller designed by using CDM technique is based on the coefficients of the characteristics polynomial of the closed loop system according to the convenient performance such as equivalent time constant, stability indices and stability limit. Controller is designed for the three tank process by using CDM Techniques; the simulation results show that the proposed control strategies have good set point tracking and better response capability.
1. The document discusses Nyquist stability criteria and polar plots.
2. Nyquist stability criteria uses Cauchy's argument principle to relate the open-loop transfer function to the poles of the closed-loop characteristic equation.
3. For a system to be stable, the number of counter-clockwise encirclements of the Nyquist plot around the point -1 must equal the number of open-loop poles in the right half plane.
This document contains lecture notes on signals, systems and transforms for a course titled EE 3054: Signals, Systems and Transforms. It covers topics in discrete-time and continuous-time signals and systems, including properties of signals and systems, convolution, Z-transforms, Laplace transforms, difference/differential equations, complex poles, frequency responses, Fourier transforms, and sampling theory. The document provides examples and homework problems for students to work through related to each major topic.
The document compares different schemes for windup protection in control systems. It tests PI and PID controllers using five different processes in simulation. Four anti-windup methods are evaluated: the back-calculation method, Dow method, Foxboro method, and Blevins method. The document finds that no single method performs best for all cases. Controller and process dynamics determine the most suitable method. Additional parameters are required for some methods. The evaluation provides insights into the advantages and disadvantages of each method for different processes and disturbances.
This document provides a list of errata for the textbook "Digital Signal Processing: A Computer-Based Approach" by Sanjit K. Mitra. It contains 22 corrections for Chapter 2, ranging from fixing equation numbers and variables to correcting program code. Similar corrections are provided for Chapters 3 through 7, with over 100 total errata listed to improve the accuracy of the textbook.
The document discusses the design of a PSO-based optimal/tunable PID fuzzy logic controller using an FPGA. It aims to reduce the complexity and improve the processing speed of PID fuzzy logic controllers. The proposed controller design includes a tuning gains block that allows for PSO optimization of scaling gains. Two versions are designed - an 8-bit and 6-bit PIDFC. The PSO algorithm is used to tune controller parameters to minimize error and find optimal gains. Block and structure diagrams of the PIDFC integrated into a feedback control system are presented.
This document proposes a two-level optimization method for tuning PID controllers to account for nonlinear system behavior. The first level uses classical tuning guidelines to determine bounds on PID parameters. The second level solves an optimization problem to determine PID parameters that minimize the difference between the closed-loop response of a designed nonlinear controller and the PID controller, subject to constraints based on the first level bounds. The method is demonstrated on a nonlinear chemical reactor example. In summary, the method tunes PID controllers to better emulate the performance of a designed nonlinear controller while respecting constraints from classical linear tuning methods.
This document lists various engineering courses taught by Kevin D. Donohue and provides links to course materials including syllabi, lecture notes, assignments, and supplemental files. Courses cover topics in circuits, signals and systems, electronics laboratory, and communications and signal processing. For each course, the instructor has made available resources to aid student learning such as notes, examples, projects and Matlab/Labview files.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
1. MODEL-BASED AUTOTUNING SYSTEM
USING ANN AND RELAY FEEDBACK TEST
Hsiao-Ping Huang 1
Jyh-Cheng Jeng
Feng-Yi Lin
Department of Chemical Engineering
National Taiwan University
Taipei 10617, Taiwan
Abstract: A model-based autotuning system is presented for PI/PID controllers. A
conventional relay feedback test is used to generate the response for estimations of
parameters such as: process gain, ultimate gain, ultimate frequency, and apparent
deadtime. Two ANNs are built based on the data generated from standard SOPDT
processes to enhance the estimation of apparent deadtime. Upon having the
estimated results, the dynamics of the process is classified into one of two groups. In
one group, PI/PID controller will be tuned based on the FOPDT parameterization.
In the other group, only PID controller will be considered for dynamic control, and
the controller will be tuned according to the SOPDT parameterization. The tuning
rules are given in terms of ultimate gain, ultimate frequency, and the apparent
deadtime. Since the tuning rules are derived from model-based control, they are
superior to the Z-N rules in performance.
Keywords: relay feedback, autotuning, ANN, FOPDT, SOPDT
1. INTRODUCTION
In 1984, ˚Astr¨om and H¨agglund (1984) presented a
relay feedback system to generate sustained oscilla-
tion as an alternative to the conventional continuous
cycling technique for controller tuning. This relay
feedback test was soon referred as autotune varia-
tion (ATV) (Luyben, 1987). As shown in Fig. 1(a)
is the block diagram of the ATV loop. Figure 1(b)
illustrates the typical response curves from the ATV
system. The test provides ultimate gain (kcu) and
ultimate period (Pu) of the following to apply Ziegler-
Nichols method for controller tuning.
kcu =
4h
πA
; ωu =
2π
Pu
(1)
Controller tuning via the above mentioned ATV test
is attractive, because it is operated under closed-loop
and no a priori knowledge of system is need. But, the
control performance thus obtained is, in general, infe-
rior to those tuned by model-based, such as IMC and
other related methods. This fact is most obvious when
the processes have significantly underdamped and
second-order dynamics. To employ model-based tun-
ing, an adequate and reduced order dynamic model
1 Corresponding author. E-mail:huanghpc@ntu.edu.tw
(usually, FOPDT or SOPDT) is required. In litera-
ture, there are reported efforts (Luyben, 1987; Li et
al., 1991; Chang et al., 1992; Wang et al., 1997; Huang
et al., 2000; Kaya and Atherton, 2001; Huang and
Jeng, 2003) trying to develop such models from the
ATV tests. Nevertheless, according to those reports
in literature, two major difficulties are encountered.
One of difficulties is that estimation of ultimate gain
and frequency according to Eq.(1) is subject to errors,
sometimes as high as 20 percent for ultimate gain (Li
et al., 1991). The second difficulty is due to the fact
that one simple ATV test, in general, does not provide
sufficient data for identifying a parametric model
aforementioned. Improvements to give better accu-
racy and efficiency by using saturation relay (Shen et
al., 1996) or by reducing high-order harmonic terms
using the Fourier analysis (Lee et al., 1995; Sung and
Lee, 1997; Wang et al., 1997) have also been reported.
But, these does not alter the encountered second
difficulty above mentioned. To overcome the second
difficulty, more than one ATV test is usually required
(Li et al., 1991; Scali et al., 1999). In order to have the
superior performance that the model-based controller
used to have, while having the simple experiment
like the conventional autotuning via ATV, a new
autotuning method is presented.
2. (a)
Gp(s)hR yu
ProcessRelay
+
−
(b)
y
u
t
t
Tp
θo A
Pu
h
θ
Aθ
Fig. 1. (a) Block diagram of a relay feedback system
(b) Response curves in relay feedback test
In the following, it is assumed that zero offset is a
common specification of control. For zero offset, in
general, PI or PID controller is considered for control.
Usage of either type of the controllers mentioned
depends not only on the application occasions, but
also on their dynamic characteristics. Thus, an au-
totuning system should provide the best flexibility
to cope with the application demand and the dy-
namics. For this purpose, model-based tuning rules
including PI and PID controllers are considered, and,
classification based on the dynamics of the processes
into two groups for controller tuning is presented.
The first group of processes are suitable for either PI
or PID controllers for dynamic compensations, and,
the tuning formula are derived based on an FOPDT
model. The second group of processes, on the other
hand, are considered good only for PID controllers
which are derived based on an underdamped SOPDT
model. Identification for classification of these two
groups is thus presented. Since the apparent deadtime
of process is crucial for applying the proposed classifi-
cation, a novel approach enhanced by artificial neural
network for estimation of the apparent deadtime is
presented. The autotuning procedure starts with an
ATV test. The steady-state gain, kp, and kcu are
estimated along with the experiment until constant
cycling occurs. The constant cycles at the output are
then used to estimate the apparent deadtime, and
the process is classified for tuning. After classifying to
either of the two groups, model-based tuning rules are
assigned and the controller parameters are computed
accordingly. Several examples are used to illustrate
this proposed method.
2. MODEL-BASED CONTROLLERS DESIGN
In general, models with dynamics up to second order
plus deadtime are adequate for designing PI/PID
controllers. For higher order processes, dynamics are
usually represented by reduced order models of the
following:
• FOPDT Gp(s) =
kp e−θs
τs + 1
(2)
• SOPDT Gp(s) =
kp e−θs
τ2s2 + 2τζs + 1
(3)
2.1 Tuning PI/PID based on FOPDT model
A direct synthesis approach is used to synthesize
PI/PID controller using an FOPDT parameteriza-
tion. In case of demanding for a PI controller, the
controller is devised so as to compensate the process
dynamics to have a loop transfer function (LTF) of
the following standard form:
Gloop(s) =
ko
θ
e−θs
s
(4)
In those cases that demand for a PID controller, LTF
is chosen to be compensated the process to become:
Gloop(s) =
ko
θ
(1 + aθs)
s (1 + τf s)
e−θs
(5)
The use of loop transfer function in the form of Eq.(4)
or Eq.(5) has been explained in a late work of Huang
and Jeng (2002). According to the standard forms,
parameters of the PI/PID controllers can be derived
as following:
kc =
ko τ
kp θ
; τR = τ ; τD = a θ (6)
Notice that the PID controller used here is the actual,
or series, form. In this tuning, ko and a are parameters
for performance or robustness specification, and the
filter time constant, τf , is taken arbitrarily small
(e.g. 0.05τD). The defaulted values of ko and a are
suggested as 0.65 and 0.4, respectively, for the PID
controller. On the other hand, the defaulted values
of ko for the PI controller are 0.5. These defaulted
values will provide about 3 and 60◦
as gain and phase
margin of the system, respectively.
Using ultimate gain and ultimate frequency, the tun-
ing formula of Eq.(6) that are originally in terms of
the FOPDT parameterization can be re-written as:
kc =
ko Ku
2
− 1
kp[π − tan−1
( Ku
2
− 1)]
τR =
Ku
2
− 1
ωu
τD = a
π − tan−1
( Ku
2
− 1)
ωu
(7)
where Ku = kpkcu.
3. 2.2 Tuning PID based on SOPDT model
The PID controller in terms of SOPDT parameter-
ization is derived in the similar way to give a loop
transfer function of Eq.(4). The resulting controller
parameters are given as:
kc =
ko (2τζ)
kp θ
; τR = 2τζ ; τD =
τ
2ζ
(8)
In this case, the controller is an ideal PID. As has
been mentioned, the defaulted value of ko is taken
as 0.5. As a result, in terms of the ultimate gain and
ultimate frequency, the PID parameters of Eq.(8) can
be written as:
kc =
ko Ku sin(ωuθ)
kp ωu θ
τR =
Ku sin(ωuθ)
ωu
τD =
1 + Ku cos(ωuθ)
ωuKu sin(ωuθ)
(9)
If kcu and ωu of the given process are obtained
from ATV test, the parameters of the PI or PID
controllers can be computed based on either Eq.(7)
or Eq.(9). However, as one can seen in Eq.(9), the
tuning formula need to know the values of kp and the
apparent deadtime θ in advance. The estimation for
kp and θ will be given in the next section.
3. PROCESS IDENTIFICATION USING ATV
TEST
To apply the model-based controllers derived in the
previous section, reduced order dynamic models pa-
rameterized as FOPDT of Eq.(2), and, as SOPDT of
Eq.(3) are required. An ATV response is thus used
to develop such parametric models. As shown in Fig.
1(a) is a ATV system which consists of process, Gp,
and a relay controller. The relay controller provides
output at +h or −h only as on-off control. The
controlled process output consists of transient oscilla-
tions after a pure deadtime, θo
, and develops constant
cycling with magnitude, A, and period, Pu. Notice
that A and Pu are used in the autotuning system of
˚Astr¨om and H¨agglund (1984) to apply Z-N method
to compute the PI/PID controller parameters. In
the meantime, Tp, θ and an associated height, Aθ,
within one of the constant cycles are also indicated
in Fig. 1(b). Here, θ is used to designate an apparent
deadtime in the FOPDT or the SOPDT model, which
is used to represent the dynamics of higher order
processes. All these quantities measured from an ATV
response are governed by the dynamic model and the
relay. In other words, they can be expressed as:
A
kph
= f1(¯τ) or f1(¯τ, ζ) (10)
Pu
θ
= f2(¯τ) or f2(¯τ, ζ) (11)
Aθ
A
= f3(¯τ) or f3(¯τ, ζ) (12)
θ
Tp
= f4(¯τ) or f4(¯τ, ζ) (13)
where ¯τ represents τ/θ. The equations given above
describe the dynamic features of the ATV response
in time domain. Two equations which correspond to
Eqs.(10) and (11) derived from frequency domain are:
ωuθ + tan−1 2 ωuτζ
1 − ωu
2τ2
= π (14)
kp
(1 − ωu
2τ2)2 + 4 ωu
2τ2ζ2
=
1
kcu
(15)
where ωu is taken as 2π/Pu.
Theoretically, provided that kp and kcu are given,
the identification problem to find an reduced or-
der SOPDT model can be solved by finding τ, ζ,
and θ that fit Eqs.(10)-(13) or Eqs.(12)-(15) in the
sense of least-squares. The explicit functional forms
for Eqs.(10) -(13) are not available, and numerical
method to solve the above equations will not be
convenient. Since estimation of apparent deadtime θ
as well as kp and kcu is required for this proposed
autotuning method, in the following, a simplified al-
gorithm will be presented to estimate these required
data from ATV test.
3.1 Estimation of kp and kcu
To estimate kp, the experimental ATV test is started
with a temporal disturbance to either the set-point
or the process input (i.e. u) for a short period of
time and restored back to its origin. The disturbance
introduced has two main purposes. One is to initialize
the relay feedback control, the other one is to generate
data for computing the steady-state process gain, kp.
The estimation is made along the ATV test in one
run as the following.
Let yI
and uI
designate the integrations of y and u
from the very beginning of the experiment in one run.
That is:
yI
(t) =
t
0
y(τ) dτ ; uI
(t) =
t
0
u(τ) dτ (16)
For some t > T when y in an ATV test starts to
oscillate with constant period and amplitude, yI
and
uI
will have similar cycling responses. Let yI
av and
uI
av designate the average heights of constant cycles
of yI
and uI
, respectively. The value of kp can be
estimated as:
kp =
yI
av
uI
av
(17)
On the other hand, due to the use of describing func-
tion for estimation, the ultimate gain computed from
4. Eq.(1) is subjected to error, which may, sometimes,
be as high as 20%. For tuning purpose, estimation
of the ultimate gain kcu with improved accuracy is
desirable. Since u(t) and y(t) are periodic with period
Pu, they can be expanded into Fourier series. If the
first harmonics are extracted, their coefficients give
one point of process frequency response at ultimate
frequency ωu via the following equation (Wang et
al., 1997):
Gp(jωu) =
t0+Pu
t0
y(t) e−jωut
dt
t0+Pu
t0
u(t) e−jωut dt
(18)
where t0 is taken as any time instant in a constant
cycle. Then, the ultimate gain can be computed
exactly as:
kcu =
1
|Gp(jωu)|
(19)
3.2 Estimation of apparent deadtime
The apparent deadtime is the deadtime appearing in
an FOPDT or SOPDT model that approximates best
the higher order process. As a result, this apparent
deadtime differs, in general, from its true deadtime
which is designated as θo
and can be detected at the
very beginning of the test. Features in the cycling
response can be used to distinguish the FOPDT from
SOPDT dynamics. For example, in case of FOPDT
process, Tp equals θo
or θ. The same equality does
not apply to the SOPDT case. In an ATV test,
two measured quantities, Aθ/A and θ/Tp, are used
to characterize the effect of the apparent deadtime.
These two quantities, as mentioned earlier, are func-
tions of ¯τ and ζ. To explore their functional relations,
simulations of ATV tests on the standard SOPDT
processes covering wide range of ¯τ (in dimensionless
form) and ζ are carried out. Results of Aθ/A and
θ/Tp for underdamped SOPDT processes are plotted
as a graph as shown in Fig. 2(a), using ¯τ and ζ as
parameters. Each pair of the two measured quantities
corresponding to a point in the graph, where a specific
pair of values for ¯τ and ζ can be found. As shown
in the figure, it is difficult to read ¯τ and ζ from
the figure. In order to make each curve in Fig. 2(a)
more readable, the coordinate is rotated through the
following transformation.
X =
θ
Tp
cos(π/3) −
Aθ
A
sin(π/3)
Y =
θ
Tp
sin(π/3) +
Aθ
A
cos(π/3)
(20)
The results are plotted in Fig. 2(b). Moreover, for
applying these data efficiently, two artificial neural
networks (ANN) are constructed. The network ar-
chitecture is as shown in Fig. 3. These two neural
networks are fed with X and Y , and compute ¯τ and
ζ, respectively. Each network consists of feedforward
net with one input layer, one hidden layer, and one
(a)
0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0.4
0.5
0.6
0.7
0.8
0.9
1
θ / Tp
Aθ
/ A
τ = 1.0
0.9
0.8
0.7
0.6
0.5
1.5
3.0
2.0
Solid line : equal τ
Dashed line : equal ζ
( ζ = 0.05, 0.1, 0.5, 1.0; from up to down )
1.1
1.2
1.3
1.4
(b)
−0.42 −0.4 −0.38 −0.36 −0.34 −0.32
0.7
0.8
0.9
1
1.1
1.2
1.3
X
Y
ζ = .05
ζ = 1.0
τ = 1.0
1.5
0.8
1.1
1.2
1.3
1.4
0.50.1
0.9
0.7
0.3
Fig. 2. Results of Aθ/A and θ/Tp in the ATV test for
SOPDT processes (a) original (b) transformed
Σ
Σ
Σ
f1
f1
f1
Σ f2
weights
bias
weights
bias
X
Y
¯τ (or ζ)
.....
...........Input Hidden Layer Output Layer
.....
.....
Fig. 3. Neural network architecture
output layer. The sigmoid function f is used in an er-
ror backpropagation technique to minimize the error
between prediction and target values.
With these two networks, estimation of the apparent
deadtime can be proceeded. The estimation makes
uses of the phase criterion in Eq.(14). Notice that
three unknowns are required to satisfy at least four
functional relations (i.e. Eqs.(10)-(13) or Eqs.(12)-
(15)), and iterative check is thus necessary to find the
solution in a least-squares sense. By solving Eqs.(12)-
(14), a unique solution for τ, ζ, and θ can be found.
But, the resulting solution may not necessarily satisfy
Eq.(15). The final solution needs further iterative
procedures. To satisfy the extra Eq.(15), it is found
that manifold in the space of τ and ζ results from the
relation of the following:
tan−1 2ωuτζ
1 − ωu
2τ2
= π − ωuθ (21)
With ωu and θ being fixed, there are many pairs of
τ and ζ that satisfy Eq.(14), and one of these pairs
would make Eq.(15) satisfied. However, in this pro-
posed autotuning system, only the apparent deadtime
5. 0 1 2 3 4 5 6 7 8 9 10
0.6
0.8
1
1.2
1.4
1.6
1.8
2
θ / τ
K
u
ζ = 0.4
0.5
0.6
0.7
0.8
0.9
1.1
1.0
Fig. 4. Ku for different SOPDT processes
of the process is required, estimation of the exact
values of τ and ζ can be skipped except a complete
process model is desired.
With the theory presented above, the algorithm for
the estimation of apparent deadtime can be made in
a simpler way as the following:
1) Starting from a guessed value of θ, which is
initially taken as θo
.
2) The values of X and Y are calculated and fed
into two networks. Then, parameters ¯τ and ζ
are computed, and check if Eq.(14) holds. The
procedure proceeds iteratively by increasing the
guess value of θ until θ equals Tp.
3) When, at certain value of guessed θ, Eq.(14)
holds true, the resulting guess value θ is taken
as the estimated value of apparent deadtime.
4) If, until the guessed value of θ exceeds Tp and no
candidate solution is found, the underdamped
SOPDT model is not good for describing the
dynamics of the process. As a result, model of
FOPDT or overdamped SOPDT should be used.
3.3 Classification for controller tuning
In general, processes with SOPDT dynamics, which
are overdamped or slightly underdamped, are some-
times identified with FOPDT models for controller
design without significant difference in performance.
It is thus curious to know under what condition can
an SOPDT process has controller parameters in terms
of an FOPDT parameterization. The result in Eq.(7)
indicates that it is necessary with Ku > 1. As shown
in Fig. 4, Ku of SOPDT processes is plotted against
θ/τ using ζ as a parameter. It is found that Ku > 1
happens when ζ ≥ 0.7. Thus, the uses of Eq.(7) and
of Eq.(9) for controller tuning are discriminated using
ζ = 0.7 as a boundary. As mentioned earlier, from
the ATV test, it provides A/(kph) and Pu/θ which
are functions of ¯τ and ζ. As shown in Fig. 5, there
are two curves that correspond to SOPDT processes
with ζ = 0.7 (curve A) and FOPDT processes (curve
B). Curve A and curve B are found to be represented,
respectively, by the following equations:
Ω = 0.465Λ3
− 2.002Λ2
+ 0.958Λ − 0.007 (22)
Ω = 30.93Λ3
− 56.78Λ2
+ 29.03Λ − 4.51 (23)
10
0
10
1
10
2
10
−2
10
−1
10
0
P
u
/ θ
A / (kp
h)
Zone I
Zone II
FOPDT
(Curve B)
SOPDT
(Curve A)
ζ = 0.7
Fig. 5. Curves for process classification
where Ω = log(A/kph) and Λ = log(Pu/θ). These two
curves divide the graph of Fig. 5 into two zones. One
is between the curve A and curve B (i.e. Zone I) that
represents the feasible region for using parameteriza-
tion of FOPDT due to ζ ≥ 0.7, and the other region
above curve A (i.e. Zone II) that represents the fea-
sible region to use parameterization of underdamped
SOPDT. Thus, once kp and the apparent deadtime
θ are obtained, the normalized value of A/(kph) and
Pu/θ can be calculated. Then, compare the resulting
value of log(A/kph) with the one calculated from
Eq.(22). If the former is smaller, then this process
is classified into the group (Group I) where Eq.(7)
applies to tune PI/PID controllers. Otherwise, the
process is classified into the other group (Group II)
where Eq.(9) will be used for tuning PID controllers.
4. AUTOTUNING PROCEDURES WITH
ILLUSTRATED EXAMPLES
To perform the autotuning, the relay feedback of the
ATV test is initialized by a short period of manual
disturbance. After the response has constant cycling,
A and Pu are recorded, and the following procedure
steps are taken:
1) Compute kp from Eq.(17) and kcu from Eq.(19).
2) Estimate the apparent deadtime θ.
3) Having the values of kp and θ, the process is clas-
sified by comparing the value of A/(kph) from
ATV test with the one calculated by Eq.(22).
4) If the process belongs to Group I, Eq.(7) is
used for tuning PI or PID controllers. Otherwise,
Eq.(9) is used to tune a PID controller.
Notice that, in case of significantly overdamped dy-
namics, the trajectory of the (θ/Tp, Aθ/A) will be
crowded at the lower edge of the graph in Fig. 2(a).
In that case, the process can be classified into Group
I directly without estimating the apparent deadtime.
For practical application, the issue to be considered is
the measurement noise. When the measured signals
are blurred with noise, data used in the proposed
method are taken as the average values of measure-
ments from several constant cycles to ensure the
success of this autotuning.
In order to illustrate the above autotuning proce-
dures, a few examples are used for simulation. The
results of applying proposed autotuning method are
6. Table 1. Results of autotuning for simulated processes
ATV test Estimated parameters Controller tuning
Example Process
A Pu kp kcu θ
Classification
kc τR τD
1 e−1.5s
(s+1)5 0.72 12.14 1.01 1.81 2.91 Group I 0.46 2.96 1.66
2
(0.5s+1) e−s
(s+1)2(2s+1)
0.35 6.56 1.0 3.74 1.32 Group I 1.29 3.78 0.77
kc τR τD
3 e−2s
(9s2+2.4s+1)(s+1)
1.17 15.90 1.0 1.11 2.72 Group II 0.45 2.47 3.96
(a)
0 20 40 60 80 100 120
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Time
Output
Proposed
Z−N
(b)
0 10 20 30 40 50 60
0
0.5
1
1.5
Time
Output
Proposed
Z−N
(c)
0 20 40 60 80 100 120 140 160 180 200
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Time
Output
Proposed
Z−N
Fig. 6. Control responses of (a) Example 1 (b) Exam-
ple 2 (c) Example 3
summarized in Table 1. The control results using
proposed model-based method and Z-N method are
shown in Fig. 6. Notice that the Z-N settings are
obtained from the same set of experiment data. These
results show that the proposed method can give more
satisfactory control performance than conventional
autotuning system.
5. CONCLUSIONS
In this paper, a systematic procedure is used to per-
form the autotuning of PI/PID controllers using one
ATV experiment. The usage of PI or PID controller
depends on the control application and on the dy-
namic characteristics of the process. The autotuning
system considered the effective damping factor for
classifying the process into one of two groups. In
either case, besides parameters kp and θ, the tun-
ing formula are given in terms of ultimate gain and
ultimate frequency obtained from a constant cycle.
These parameters can be estimated within one ATV
experiment. Two ANNs are constructed to enhance
the estimation of apparent deadtime. The simulation
results have shown that this proposed autotuning
system is efficient and self-contained.
ACKNOWLEDGMENT
The authors thank R. C. Panda (CLRI/CSIR, India)
for the help in constructing the ANNs.
This work is supported by the National Science
Council of Taiwan under Grant no. NSC 92-2214-E-
002-013.
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