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.
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.
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...IJECEIAES
In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations.
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.
Decentralized supervisory based switching control for uncertain multivariable...ISA Interchange
In this paper, the design of decentralized switching control for uncertain multivariable plants is considered. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model and specific control structure. The underlying design is based on the quantitative feedback theory (QFT). It is assumed that a MIMO-QFT controller exists for robust stability and performance of the individual uncertain sets. The proposed control structure is made up by these local decentralized controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the local models’ behaviors with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down the switching to guarantee the overall closed loop stability. It is shown that this strategy provides a stable and robust adaptive controller to deal with complex multivariable plants with input–output pairing changes during the plant operation, which can facilitate the development of a reconfigurable decentralized control. Also, the multirealization technique is used to implement a family of controllers to achieve bumpless transfer. Simulation results are employed to show the effectiveness of the proposed method.
In this paper, the design of a speed control scheme based on a total sliding mode control for Indirect Field Oriented of a three phase induction motor (IM) is proposed. Firstly, the indirect field oriented control is derived. Then, sliding mode control design is investigated to achieve a speed tracking objective under different load torque disturbance. Finally a dSPACE DS1104 R&D board is used to implement the proposed scheme. The experimental results released on 0.25 kW slip-ring IM show a high dynamic performance, fast transient response without overshot as well as a good load disturbances rejection response.
Tracy–Widom distribution based fault detection approach: Application to aircr...ISA Interchange
The fault detection approach based on the Tracy–Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy–Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined.
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.
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...IJECEIAES
In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations.
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.
Decentralized supervisory based switching control for uncertain multivariable...ISA Interchange
In this paper, the design of decentralized switching control for uncertain multivariable plants is considered. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model and specific control structure. The underlying design is based on the quantitative feedback theory (QFT). It is assumed that a MIMO-QFT controller exists for robust stability and performance of the individual uncertain sets. The proposed control structure is made up by these local decentralized controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the local models’ behaviors with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down the switching to guarantee the overall closed loop stability. It is shown that this strategy provides a stable and robust adaptive controller to deal with complex multivariable plants with input–output pairing changes during the plant operation, which can facilitate the development of a reconfigurable decentralized control. Also, the multirealization technique is used to implement a family of controllers to achieve bumpless transfer. Simulation results are employed to show the effectiveness of the proposed method.
In this paper, the design of a speed control scheme based on a total sliding mode control for Indirect Field Oriented of a three phase induction motor (IM) is proposed. Firstly, the indirect field oriented control is derived. Then, sliding mode control design is investigated to achieve a speed tracking objective under different load torque disturbance. Finally a dSPACE DS1104 R&D board is used to implement the proposed scheme. The experimental results released on 0.25 kW slip-ring IM show a high dynamic performance, fast transient response without overshot as well as a good load disturbances rejection response.
Tracy–Widom distribution based fault detection approach: Application to aircr...ISA Interchange
The fault detection approach based on the Tracy–Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy–Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined.
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
On an LAS-integrated soft PLC system based on WorldFIP fieldbusISA Interchange
Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable.
Modeling and Control of MIMO Headbox System Using Fuzzy LogicIJERA Editor
The Headbox plays an important role in pulp supply system with sheet forming in paper making process. The air cushion headbox is a nonlinear & strong coupling system. In the air cushion headbox system there were two important parameters which include total head and the stock level for improving pulp product quality. These two parameters make this system MIMO output system so for this a decoupling controls strategy was required for interaction between these two control loops. In this paper fuzzy tuned PID control scheme is proposed for controlling the nonlinear control problem in air cushion headbox after the system being decoupled. An attempt has been made for comparison between classical (PID) and fuzzy tuned PID controller. It concludes that the fuzzy tuned PID controller is found most suitable for MIMO system in terms of obtaining steady state properties. The effects of disturbances are studied through computer simulation using Matlab/Simulink toolbox.
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
Neural Network Control Based on Adaptive Observer for Quadrotor HelicopterIJITCA Journal
A neural network control scheme with an adaptive observer is proposed in this paper to Quadrotor helicopter stabilization. The unknown part in Quadrotor dynamical model was estimated on line by a Single Hidden Layer network. To solve the non measurable states problem a new adaptive observer was proposed. The main purpose here is to reduce the measurement noise amplification caused by conventional high gain observer by introducing some changes in observer’s original structure that can minimize the variance and the amplitude of the noisy signal without increasing tracking error. The stability analysis of the overall closed-loop system/ observer is performed using the Lyapunov direct method. Simulation results are given to highlight the performances of the proposed scheme
PI and fuzzy logic controllers for shunt active power filterISA Interchange
This paper presents a shunt Active Power Filter (APF) for power quality improvements in terms of harmonics and reactive power compensation in the distribution network. The compensation process is based only on source current extraction that reduces the number of sensors as well as its complexity. A Proportional Integral (PI) or Fuzzy Logic Controller (FLC) is used to extract the required reference current from the distorted line-current, and this controls the DC-side capacitor voltage of the inverter. The shunt APF is implemented with PWM-current controlled Voltage Source Inverter (VSI) and the switching patterns are generated through a novel Adaptive-Fuzzy Hysteresis Current Controller (A-F-HCC). The proposed adaptive-fuzzy-HCC is compared with fixed-HCC and adaptive-HCC techniques and the superior features of this novel approach are established. The FLC based shunt APF system is validated through extensive simulation for diode-rectifier/R–L loads.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
PID controller for microsatellite yaw-axis attitude control system using ITAE...TELKOMNIKA JOURNAL
The need for effective design of satellite attitude control (SAC) subsystem for a microsatellite is imperative in order to guarantee both the quality and reliability of the data acquisition. A proportional-integral-derivative (PID) controller was proposed in this study because of its numerous advantages. The performance of PID controller can be greatly improved by adopting an integral time absolute error (ITAE) robust controller design approach. Since the system to be controlled is of the 4th order, it was approximated by its 2nd order version and then used for the controller design. Both the reduced and higher-order pre-filter transfer functions were designed and tested, in order to improve the system performance. As revealed by the results, three out of the four designed systems satisfy the design specifications; and the PD-controlled system without pre-filter transfer function was recommended out of the three systems due to its structural simplicity, which eventually enhances its digital implementation.
Formulation of Generalized Block Backstepping Control Law of Underactuated Me...Shubhobrata Rudra
A Generalized Block Backstepping Control law has been presented to address the control problem of different types of underactuated systems. In addition, if the concerned system is strong inertially coupled then the proposed algorithm is strong enough to ensure global asymptotic stability of the system.
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.
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.
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.
Adaptive control of nonlinear system based on QFT application to 3-DOF flight...TELKOMNIKA JOURNAL
Research on unmanned aerial vehicle (UAV) became popular because of remote flight access and
cost-effective solution. 3-degree of freedom (3-DOF) unmanned helicopters is one of the popular research
UAV, because of its high load carrying capacity with a smaller number of motor and requirement of
forethought motor control dynamics. Various control algorithms are investigated and designed for the motion
control of the 3DOF helicopter. Three-degree-of-freedom helicopter model configuration presents the same
advantages of 3-DOF helicopters along with increased payload capacity, increase stability in hover,
manoeuvrability and reduced mechanical complexity. Numerous research institutes have chosen
the three-degree-of-freedom as an ideal platform to develop intelligent controllers. In this research paper,
we discussed about a hybrid controller that combined with Adaptive and Quantitative Feedback theory (QFT)
controller for the 3-DOF helicopter model. Though research on Adaptive and QFT controller are not a new
subject, the first successful single Adaptive aircraft flight control systems have been designed for the U.S.
Air Force in Wright Laboratories unmanned research vehicle, Lambda [1]. Previously researcher focused on
structured uncertainties associated with controller for the flight conditions theoretically. The development of
simulationbased design on flight control system response, opened a new dimension for researcher to design
physical flight controller for plant parameter uncertainties. At the beginning, our research was to investigates
the possibility of developing the QFT combined with Adaptive controller to control a single pitch angle that
meets flying quality conditions of automatic flight control. Finally, we successfully designed the hybrid
controller that is QFT based adaptive controller for all the three angles.
Development of a Customized Autopilot for Unmanned Helicopter Model Using Gen...Ahmed Momtaz Hosny, PhD
The objective of this paper is to develop a customized autopilot system that enables a helicopter model to carry out an autonomous flight using on-board microcontroller. The main goal of this project is to provide a comprehensive controller design methodology, Modeling, simulation, guidance and verification for an unmanned helicopter model. The autopilot system was designed to demonstrate autonomous maneuvers such as flying over the planned waypoints with constant forward speed.
Fuzzy based control using labview for miso temperature processeSAT Journals
Abstract This project aims at designing and implementing a fuzzy controller for Multiple Input Single Output temperature process. Temperature control of water in the tank is achieved by varying current to the heating rod and inlet flow rate by a fuzzy controller. The system consists of a tank, reservoir, variable speed pump, temperature sensor placed inside a heating tank containing the heating rod, voltage controlled current source and computer. Water is pumped into the tank from reservoir and RTD measures the current temperature. The signal from the temperature sensor is sent to the DAQ interfaced to the computer. LabVIEW software is used to acquire the input signal and send the output signal that is determined by the control algorithm. Fuzzy logic controller is designed in LabVIEW. Based on the set point temperature, the controller sets the appropriate current to the heating rod. If the required temperature is less than that sensed by the temperature sensor, the flow rate of water into the tank is controlled by a variable speed pump. While conventional controllers are analytically described by a set of equations, the FLC is described by a knowledge-based algorithm. Thus this system is highly efficient in both heating and reducing the temperature of the tank. A fuzzy logic controller gives faster response, is more reliable and recovers quickly from system upsets. It also works well to uncertainties in the process variables and it does not require mathematical modelling.
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
On an LAS-integrated soft PLC system based on WorldFIP fieldbusISA Interchange
Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable.
Modeling and Control of MIMO Headbox System Using Fuzzy LogicIJERA Editor
The Headbox plays an important role in pulp supply system with sheet forming in paper making process. The air cushion headbox is a nonlinear & strong coupling system. In the air cushion headbox system there were two important parameters which include total head and the stock level for improving pulp product quality. These two parameters make this system MIMO output system so for this a decoupling controls strategy was required for interaction between these two control loops. In this paper fuzzy tuned PID control scheme is proposed for controlling the nonlinear control problem in air cushion headbox after the system being decoupled. An attempt has been made for comparison between classical (PID) and fuzzy tuned PID controller. It concludes that the fuzzy tuned PID controller is found most suitable for MIMO system in terms of obtaining steady state properties. The effects of disturbances are studied through computer simulation using Matlab/Simulink toolbox.
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
Neural Network Control Based on Adaptive Observer for Quadrotor HelicopterIJITCA Journal
A neural network control scheme with an adaptive observer is proposed in this paper to Quadrotor helicopter stabilization. The unknown part in Quadrotor dynamical model was estimated on line by a Single Hidden Layer network. To solve the non measurable states problem a new adaptive observer was proposed. The main purpose here is to reduce the measurement noise amplification caused by conventional high gain observer by introducing some changes in observer’s original structure that can minimize the variance and the amplitude of the noisy signal without increasing tracking error. The stability analysis of the overall closed-loop system/ observer is performed using the Lyapunov direct method. Simulation results are given to highlight the performances of the proposed scheme
PI and fuzzy logic controllers for shunt active power filterISA Interchange
This paper presents a shunt Active Power Filter (APF) for power quality improvements in terms of harmonics and reactive power compensation in the distribution network. The compensation process is based only on source current extraction that reduces the number of sensors as well as its complexity. A Proportional Integral (PI) or Fuzzy Logic Controller (FLC) is used to extract the required reference current from the distorted line-current, and this controls the DC-side capacitor voltage of the inverter. The shunt APF is implemented with PWM-current controlled Voltage Source Inverter (VSI) and the switching patterns are generated through a novel Adaptive-Fuzzy Hysteresis Current Controller (A-F-HCC). The proposed adaptive-fuzzy-HCC is compared with fixed-HCC and adaptive-HCC techniques and the superior features of this novel approach are established. The FLC based shunt APF system is validated through extensive simulation for diode-rectifier/R–L loads.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
PID controller for microsatellite yaw-axis attitude control system using ITAE...TELKOMNIKA JOURNAL
The need for effective design of satellite attitude control (SAC) subsystem for a microsatellite is imperative in order to guarantee both the quality and reliability of the data acquisition. A proportional-integral-derivative (PID) controller was proposed in this study because of its numerous advantages. The performance of PID controller can be greatly improved by adopting an integral time absolute error (ITAE) robust controller design approach. Since the system to be controlled is of the 4th order, it was approximated by its 2nd order version and then used for the controller design. Both the reduced and higher-order pre-filter transfer functions were designed and tested, in order to improve the system performance. As revealed by the results, three out of the four designed systems satisfy the design specifications; and the PD-controlled system without pre-filter transfer function was recommended out of the three systems due to its structural simplicity, which eventually enhances its digital implementation.
Formulation of Generalized Block Backstepping Control Law of Underactuated Me...Shubhobrata Rudra
A Generalized Block Backstepping Control law has been presented to address the control problem of different types of underactuated systems. In addition, if the concerned system is strong inertially coupled then the proposed algorithm is strong enough to ensure global asymptotic stability of the system.
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.
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.
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.
Adaptive control of nonlinear system based on QFT application to 3-DOF flight...TELKOMNIKA JOURNAL
Research on unmanned aerial vehicle (UAV) became popular because of remote flight access and
cost-effective solution. 3-degree of freedom (3-DOF) unmanned helicopters is one of the popular research
UAV, because of its high load carrying capacity with a smaller number of motor and requirement of
forethought motor control dynamics. Various control algorithms are investigated and designed for the motion
control of the 3DOF helicopter. Three-degree-of-freedom helicopter model configuration presents the same
advantages of 3-DOF helicopters along with increased payload capacity, increase stability in hover,
manoeuvrability and reduced mechanical complexity. Numerous research institutes have chosen
the three-degree-of-freedom as an ideal platform to develop intelligent controllers. In this research paper,
we discussed about a hybrid controller that combined with Adaptive and Quantitative Feedback theory (QFT)
controller for the 3-DOF helicopter model. Though research on Adaptive and QFT controller are not a new
subject, the first successful single Adaptive aircraft flight control systems have been designed for the U.S.
Air Force in Wright Laboratories unmanned research vehicle, Lambda [1]. Previously researcher focused on
structured uncertainties associated with controller for the flight conditions theoretically. The development of
simulationbased design on flight control system response, opened a new dimension for researcher to design
physical flight controller for plant parameter uncertainties. At the beginning, our research was to investigates
the possibility of developing the QFT combined with Adaptive controller to control a single pitch angle that
meets flying quality conditions of automatic flight control. Finally, we successfully designed the hybrid
controller that is QFT based adaptive controller for all the three angles.
Development of a Customized Autopilot for Unmanned Helicopter Model Using Gen...Ahmed Momtaz Hosny, PhD
The objective of this paper is to develop a customized autopilot system that enables a helicopter model to carry out an autonomous flight using on-board microcontroller. The main goal of this project is to provide a comprehensive controller design methodology, Modeling, simulation, guidance and verification for an unmanned helicopter model. The autopilot system was designed to demonstrate autonomous maneuvers such as flying over the planned waypoints with constant forward speed.
Fuzzy based control using labview for miso temperature processeSAT Journals
Abstract This project aims at designing and implementing a fuzzy controller for Multiple Input Single Output temperature process. Temperature control of water in the tank is achieved by varying current to the heating rod and inlet flow rate by a fuzzy controller. The system consists of a tank, reservoir, variable speed pump, temperature sensor placed inside a heating tank containing the heating rod, voltage controlled current source and computer. Water is pumped into the tank from reservoir and RTD measures the current temperature. The signal from the temperature sensor is sent to the DAQ interfaced to the computer. LabVIEW software is used to acquire the input signal and send the output signal that is determined by the control algorithm. Fuzzy logic controller is designed in LabVIEW. Based on the set point temperature, the controller sets the appropriate current to the heating rod. If the required temperature is less than that sensed by the temperature sensor, the flow rate of water into the tank is controlled by a variable speed pump. While conventional controllers are analytically described by a set of equations, the FLC is described by a knowledge-based algorithm. Thus this system is highly efficient in both heating and reducing the temperature of the tank. A fuzzy logic controller gives faster response, is more reliable and recovers quickly from system upsets. It also works well to uncertainties in the process variables and it does not require mathematical modelling.
Una pequeña recopilación y selección de información sobre el tema de el sistema aduanero en México, seccionando los puntos más importantes y básicos a mí criterio.
Tracking and control problem of an aircraftANSUMAN MISHRA
Here our main focus is to monitor and maneuver the flight for a particular distance in a time-scale with absolute control. For this a rigorous formulation of flight mechanics and theories associated with advanced control systems are simplified and analyzed to obtain a feasible & optimized solution.
It is also important to remember that this idea basically involves handling problems of maneuvering control and other pilot-issues of an inner-loop flight-control system and does not dwell on outer loop control systems .
The operational significance of this maneuver is that it allows the pilot to slew quickly without increasing the normal acceleration and turning.
Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid...IJECEIAES
This research work introduces an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively employed to stabilize the 3DOF helicopter system.
Aircraft pitch control design using LQG controller based on genetic algorithmTELKOMNIKA JOURNAL
Designing a robust aircraft control system used to achieve a good tracking performance and stable dynamic behavior against working disturbances problem has attracted attention of control engineers. In this paper, a pitch angle control system for aircraft is designed utilizing liner quadratic Gaussian (LQG) optimal controller technique with a numerical tuning algorithm method in the longitudinal plane through cruising stage. Main design approach of LQG controller includes obtaining best weighting matrices values using trial and error method that consumes effort and takes more time, in addition, there is no guarantees to obtain optimum values for weighting matrices elements. In this research, genetic algorithm (GA) is used to optimize the state and control weighting matrices and determine best values for their elements. The proposed traditional and optimized LQG pitch controller schemes are implemented utilizing Matlab simulation tool and their performance are presented and compared based on transient and steady state performance parameters. The simulation results reveal the ability of the optimized GA_LQG controller to reject the effect of the noises in the aircraft system dynamic and achieve a good and stable tracking performance compared with that of the conventional LQG pitch control system.
This work treats the modeling and simulation of non-linear system behavior of an induction motor using backstepping sliding mode control (BACK- SMC). First, the direct field oriented control IM is derived. Then, a sliding for direct field oriented control is proposed to compensate the uncertainties, which occur in the control. Finally, the study of Backstepping sliding controls strategy of the induction motor drive. Our non linear system is simulated in MATLAB SIMULINK environment, the results obtained illustrate the efficiency of the proposed control with no overshoot, and the rising time is improved with good disturbances rejections comparing with the classical control law.
DUAL NEURAL NETWORK FOR ADAPTIVE SLIDING MODE CONTROL OF QUADROTOR HELICOPTER...ijistjournal
An adaptive sliding mode control based on two neural networks is proposed in this paper for Quadrotor stabilization. This approach presents solutions to conventional control drawbacks as chattering phenomenon and dynamical model imprecision. For that reason two ANN for each quadrotor helicopter subsystem are implemented in the control loop, the first one is a Single Hidden Layer network used to approximate on line the equivalent control and the second feed-forward Network is used to estimate the ideal corrective term. The main purpose behind the use of ANN in the second part of SMC is to minimize the chattering phenomena and response time by finding optimal sliding gain and sliding surface slope. The learning algorithms of the two ANNs (equivalent and corrective controller) are obtained using the direct Lyapunov stability method. The simulation results are given to highlight the performances of the proposed control scheme.
DUAL NEURAL NETWORK FOR ADAPTIVE SLIDING MODE CONTROL OF QUADROTOR HELICOPTER...ijistjournal
An adaptive sliding mode control based on two neural networks is proposed in this paper for Quadrotor stabilization. This approach presents solutions to conventional control drawbacks as chattering phenomenon and dynamical model imprecision. For that reason two ANN for each quadrotor helicopter subsystem are implemented in the control loop, the first one is a Single Hidden Layer network used to approximate on line the equivalent control and the second feed-forward Network is used to estimate the ideal corrective term. The main purpose behind the use of ANN in the second part of SMC is to minimize the chattering phenomena and response time by finding optimal sliding gain and sliding surface slope. The learning algorithms of the two ANNs (equivalent and corrective controller) are obtained using the direct Lyapunov stability method. The simulation results are given to highlight the performances of the proposed control scheme.
Flatness Based Nonlinear Sensorless Control of Induction Motor SystemsIAES-IJPEDS
This paper deals with the flatness-based approach for sensorless control of
the induction motor systems. Two main features of the proposed flatness
based control are worth to be mentioned. Firstly, the simplicity of
implementation of the flatness approach as a nonlinear feedback linearization
control technique. Secondly, when the chosen flat outputs involve non
available state variable measurements a nonlinear observer is used to
estimate them. The main advantage of the used observer is its ability to
exploite the properties of the system nonlinearties. The simulation results are
presented to illustrate the effectiness of the proposed approach for sensorless
control of the considered induction motor.
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.
Vibration and tip deflection control of a single link flexible manipulatorijics
In this paper, a hybrid control scheme for vibration and tip deflection control of a single link flexible
manipulator system is presented. The purpose of this control is for input tracking, vibration control of hub
angle and tip deflection control. The control scheme consists of a resonant controller and a fuzzy logic
controller (FLC).The resonant controller is used as the inner loop feedback controller for vibration control
using the resonant frequencies at different resonant modes of the system which were determined from
experiment. The fuzzy logic controller is designed as the outer loop feedback controller for the tracking
control and to achieve zero steady state error. The performance of the proposed control scheme is
investigated via simulations and the results show the effectiveness of the control scheme, in addition the
controller is tested to show it robustness using different values of payload.
Analytical Evaluation of Generalized Predictive Control Algorithms Using a Fu...inventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Matlab codes for Sizing and Calculating the Aircraft Stability & PerformanceAhmed Momtaz Hosny, PhD
Matlab codes for Sizing and Calculating the Aircraft Stability & Performance, with the knowledge of the DATCOM Results. (Simple and rapid way to analyze and evaluate the aircraft performance)
Inferring the Optimum UAV's Trajectories Configuration Over Definite Intruder...Ahmed Momtaz Hosny, PhD
Inferring the Optimum UAV's Trajectories Configuration Over Definite Intruder Paths with Multiple Random Starting Points Via Genetic Algorithm - Taking into consideration a set of synchronized UAV's - (Provided with the relevant Matlab Code).
Development of Fuzzy Logic LQR Control Integration for Full Mission Multistag...Ahmed Momtaz Hosny, PhD
This work investigates the performance on the aircraft control system during air refuel purposes of the Linear Quadratic Regulator (LQR) control alone, and the integration between fuzzy control and LQR. LQR is modern linear control that is suitable for multivariable state feedback and is known to yield good performance for linear systems or for nonlinear systems where the nonlinear aspects are presented. The fuzzy control is known to have the ability to deal with nonlinearities without having to use advanced mathematics. The LQR integrated fuzzy control (LQRIFC) simultaneously makes use of the good performance of the LQR in the region close to switching curve, and the effectiveness of the fuzzy control in region away from switching curve. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into the fuzzy control. The LQRIFC is verified by simulation to suppress the uncertain instability more effectively than the LQR alone besides minimizing the time of the mission proposed. The aerial refueling process has been divided into 3 basic stages (initial stability stage, tracking stage, alignment stage) to meet all the process requirements and constraints with minimizing the whole mission time period. GA has been used to tune the fuzzy logic controller parameters and some PID’s. The control strategy was applied to both aerial refueling methods. And the MATLAB simulation results show the validity and the efficiency of using the proposed control approach.
Development of Fuzzy Logic LQR Control Integration for Full Mission Multistag...Ahmed Momtaz Hosny, PhD
This work investigates the performance on the aircraft control system during air refuel purposes of the Linear Quadratic Regulator (LQR) control alone, and the integration between fuzzy control and LQR. LQR is modern linear control that is suitable for multivariable state feedback and is known to yield good performance for linear systems or for nonlinear systems where the nonlinear aspects are presented. The fuzzy control is known to have the ability to deal with nonlinearities without having to use advanced mathematics. The LQR integrated fuzzy control (LQRIFC) simultaneously makes use of the good performance of the LQR in the region close to switching curve, and the effectiveness of the fuzzy control in region away from switching curve. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into the fuzzy control. The LQRIFC is verified by simulation to suppress the uncertain instability more effectively than the LQR alone besides minimizing the time of the mission proposed. The aerial refueling process has been divided into 3 basic stages (initial stability stage, tracking stage, alignment stage) to meet all the process requirements and constraints with minimizing the whole mission time period. GA has been used to tune the fuzzy logic controller parameters and some PID’s. The control strategy was applied to both aerial refueling methods. And the MATLAB simulation results show the validity and the efficiency of using the proposed control approach.
DEVELOPMENT OF A NEUROFUZZY CONTROL SYSTEM FOR THE GUIDANCE OF AIR ...Ahmed Momtaz Hosny, PhD
ABSTRACT
In recent years, there has been an increasing interest in the fusion of neural networks and fuzzy logic specially in missile control problems. A technique for the preliminary design of a control system is presented using a neurofuzzy approach for a highly nonlinear MIMO 5_DOF AIM 9R model. The model reflects cross coupling effects between the longitudinal and lateral motions. Two neural network controllers are used for the low level control of each motion separately. The control effort of these networks is then blended by a fuzzy logic controller to obtain the overall control action.The fuzzy controller which is a Mamdani type inference system has 25 rule base designed to cope with model uncertainties specially in cross coupling between lateral and longitudinal motions. A computer simulation is performed to compare between various control techniques. The result showed the effectiveness of the hybrid system compared to other control strategies where fuzzy systems or neural networks are used separately.
DEVELOPMENT OF NEUROFUZZY CONTROL SYSTEM FOR THE GUIDANCE OF AIR TO AIR MISS...Ahmed Momtaz Hosny, PhD
ABSTRACT
In recent years, there has been an increasing interest in the fusion of neural networks and fuzzy logic specially in missile control problems. A technique for the preliminary design of a control system is presented using a neurofuzzy approach for a highly nonlinear MIMO 5_DOF AIM 9R model. The model reflects cross coupling effects between the longitudinal and lateral motions. Two neural network controllers are used for the low level control of each motion separately. The control effort of these networks is then blended by a fuzzy logic controller to obtain the overall control action.The fuzzy controller which is a Mamdani type inference system has 25 rule base designed to cope with model uncertainties specially in cross coupling between lateral and longitudinal motions. A computer simulation is performed to compare between various control techniques. The result showed the effectiveness of the hybrid system compared to other control strategies where fuzzy systems or neural networks are used separately.
A Comparison Study between Inferred State-Space and Neural Network Based Syst...Ahmed Momtaz Hosny, PhD
In this paper, system identifications of an unmanned aerial vehicle (UAV) based on inferred state space and multiple neural networks were presented. In this work an optimization approach was used to conclude an inferred state space and the multiple neural networks system identifications based on the genetic algorithms separately. The UAV is a multi-input multi-output (MIMO) nonlinear system. Models for such MIMO system are expected to be adaptive to dynamic behavior and robust to environment.
A Comparison Study between Inferred State-Space and Neural Network Based Syst...Ahmed Momtaz Hosny, PhD
Abstract:
In this paper, system identifications of an unmanned aerial vehicle (UAV) based on inferred state space and multiple neural networks were presented. In this work an optimization approach was used to conclude an inferred state space and the multiple neural networks system identifications based on the genetic algorithms separately.
The presented work is focusing on an inferred state space based system identification which is a new approach seldom used, but it is also easier and more stable compared with the multi-network based system identification during the modeling of dynamic behavior of nonlinear systems.
The objective of this paper is to develop a customized autopilot system that enables a helicopter model to carry out an autonomous flight using on-board microcontroller. The main goal of this project is to provide a comprehensive controller design methodology, Modeling, simulation, guidance and verification for an unmanned helicopter model. The autopilot system was designed to demonstrate autonomous maneuvers such as flying over the planned waypoints with constant forward speed and considerable steep maneuvers. For the controller design, the nonlinear dynamic model of the Remote Control helicopter was built by employing Lumped Parameter approach comprising of four different subsystems such as actuator dynamics, rotary wing dynamics, force and moment generation process and rigid body dynamics. The nonlinear helicopter mathematical model was then linearized using small perturbation theory for stability analysis and linear feedback control system design. The linear state feedback for the stabilization and control of the helicopter was derived using Pole Placement Method. The overall dynamic system control with output feedback was computed using Genetic Algorithm. Series of Matlab-Simulink models and guidance algorithms were presented in this work to simulate and verify the autopilot system performance. The proposed autopilot has shown acceptable capability of stabilizing and controlling the helicopter during tracking the desired waypoints. This paper is presenting a detailed comparison study for two different guidance strategies. The first strategy is concerning the difference between the desired heading or elevation referred to the next waypoint and the actual heading or elevation of the unmanned helicopter model. The second strategy is concerning the relative distance between the actual and the desired trajectories. In other words the first method is tracking the waypoints while the second one is tracking the trajectory. In this work a comparison study was conducted through the mentioned strategies simulation to show the significant differences in the output performance. Some performance indexes were presented to evaluate the system performance errors and the control effort needed for both strategies using the same desired trajectory and the same waypoints.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
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Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
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1. Insights into SAP testing best practices
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Orchestrator execution result
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See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
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👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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https://alandix.com/academic/papers/synergy2024-epistemic/
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The Art of the Pitch: WordPress Relationships and Sales
DEVELOPMENT OF FUZZY LOGIC LQR CONTROL INTEGRATION FOR AERIAL REFUELING AUTOPILOT
1. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 1
Military Technical College
Kobry El-Kobba
Cairo, Egypt
12-th International Conference
on
Aerospace Sciences &
Aviation Technology
DEVELOPMENT OF FUZZY LOGIC LQR CONTROL
INTEGRATION FOR AERIAL REFUELING AUTOPILOT
Ahmed Momtaz*, Han Chao**
ABSTRACT
This paper investigates the performance on the aircraft control system during air
refuel purposes of the Linear Quadratic Regulator (LQR) control alone, and the
integration between fuzzy control and LQR. LQR is modern linear control that is
suitable for multivariable state feedback and is known to yield good performance
for linear systems or for nonlinear systems where the nonlinear aspects are
presented. The fuzzy control is known to have the ability to deal with
nonlinearities without having to use advanced mathematics. The LQR integrated
fuzzy control (LQRIFC) simultaneously makes use of the good performance of
the LQR in the region close to switching curve, and the effectiveness of the fuzzy
control in region away from switching curve. A new analysis of the fuzzy system
behavior presented helps to make possible precise integration of LQR features
into the fuzzy control. The LQRIFC is verified by simulation to suppress the
uncertainty instability more effectively than the LQR besides minimizing the time
of the mission proposed.
KEY WORDS
Fuzzy control, LQR, Aerial refueling, Autopilot
NOMENCLATURE
(LQR) linear quadratic regulator, (FLC) fuzzy logic controller, (COA) central of
area, (FOS) fuzzy net output signal
*PHD Candidate, School of astronautics, Beihang University, Beijing, China
**Professor, School of astronautics, Beihang University, Beijing, China
2. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 2
1. INTRODUCTION
The objective of the present work is to minimize the net performance index (PI) of
the aircraft control system during aerial refueling process by using fuzzy logic
LQR control integration instead of using LQR alone. Effectiveness of this method
is mostly appeared when the system is highly nonlinear and exposed to
surrounding uncertainty. Using of such integration permit stability and robustness
of the system specially when applying different optimization methods for fuzzy
logic parameters tuning.
2. AIRCRAFT MODELING
One of the key phases in aircraft design is the knowledge acquisition about the
aerodynamic data that can be used in all the computer oriented design
approaches, using this data the designer can build up a simulated nonlinear
model for this aircraft. For our research we had used flight aerodynamic data
given by (Brumbaugh, 1991) and (Stevens & Lewis, 1992) [1]. The employed
flight model is a stability axis model, with a state vector [α q δe αf ] for pitch rate
control and [β φ p r δa δr] for lateral control.
3. OPTIMAL FLIGHT CONTROL (LQR)
The modern control system design is based directly on the state variable model,
which contains more information about the system. Another central concept is
the expression of performance specifications in terms of a mathematically
precise performance criterion that then yields matrix equations for the control
gains. The classical successive loop closure approach means that the control
gains are selected individually. In contrast, solving matrix equations in modern
control allows all the control gains to be computed simultaneously so that all the
loops are closed at the same time with stable closed loop poles (as an algorithm
condition). This could be achieved by selecting the control input to minimize
a quadratic cost or performance index (PI) of the type
)(tu
dteVeuRuxQxJ TTT ~~
2
1
)~~~~(
2
1
0
++= ∫
∞
(1)
Where Q and R are symmetric positive semi-definite weighting matrices,
x~ , u~ , e~ are state, control, steady state error respectively
3. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 3
4. APPLYING FUZZY INFERENCE SYSTEM FOR CONTROL
The fuzzy inference technique can be very useful in control engineering. A
standard control system would utilize a numerical input and produce numerical
output and so should a fuzzy controller. The knowledge base contains the set of
inference rules chosen to achieve the control objectives and the parameters of
the fuzzy systems used to define the data manipulation in the fuzzification,
inference engine, and defuzzification processes as shown in Fig. 1. Input to the
fuzzification process is the measured or estimated variable that appears in the
antecedent part of the if-then rule. This input variable has associated linguistic
values to describe it. Each linguistic value is defined by a membership function,
parameterized by data from the knowledge base .In the inference engine the
decision–making logic is conducted, inferring control laws from the input
variables through fuzzy implication. The final step is the defuzzification process
where a crisp control command is determined based on the inferred fuzzy control
law.
4.1 Structure of Fuzzy Rules
A fuzzy rule is the basic unit for capturing knowledge in many fuzzy systems. A
fuzzy rule has two components: an if-part (also referred to as the antecedent)
and a then-rule (also referred to as the consequent):
IF <antecedent> THEN <consequent>
The antecedent describes a condition, and the consequent describes a
conclusion that can be drawn when the condition holds.
The structure of a fuzzy rule is identical to that of a conventional rule in artificial
intelligence. The main difference lies in the content of the rule antecedent. The
antecedent of the fuzzy describes an elastic condition (a condition that can be
satisfied to a degree) while the antecedent of a conventional rule describes a
rigid condition (a condition that is either satisfied or dissatisfied)[2].
4.2 Rule Derivation
Motivated by the need of a systematic method to generate and modify fuzzy rule-
bases, much research is being conducted on developing learning approaches.
This technique begins with the self-organizing controllers which consist of two
levels of fuzzy rule bases. The first rule base is the standard control fuzzy rule
4. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 4
base. The second level contains a fuzzy rule base consisting of meta-rules,
which attempt to assess the performance of the close loop control system and
subsequently used to modify the standard rule base. Learning approaches based
on evaluation theory, such as genetic algorithms[3], have a promising potential
towards the derivation of fuzzy rule bases as done in this work. Fig. 2 shows one
sort of the speed controllers that have been used utilizing both control signals
(error and error rate) according to the line of sight distance between the aircraft
and the tanker, tuning the normalized and the denormalized factors along
different operating points simulating the gain scheduling technique for the LQR
control. The result of applying COA defuzzification to a fuzzy conclusion can be
expressed by the formula:
A i
i
A i
i
( )y y
y
( )y
iμ
μ
×∑
=
∑
(2)
where Aμ is the membership of area A.
In the same manner nonlinear PID fuzzy logic controller was proposed to be
integrated with LQR controller (inner loop) for both pitch and lateral control
purposes as an outer loop control. Fig. 3 shows the different output control gains
after performing the (COA) defuzzification process for Mamdani type 49 rule
base PID nonlinear fuzzy logic controller (7X7 membership functions). The
following rules describe the logic behavior of the PID nonlinear controller as an
example, in the same way it possible to deduce the rule-base for the speed
controller.
1. if (e is NB) and (ec is NB) then (kp is PB)(Ki is NB)(Kd is PS)(1)
: : : : : : : : : :
49. if (e is PB) and (ec is PB) then (kp is NB)(Ki is PB)(Kd is PB)(1)
5. THE LQR INTEGRATED FUZZY CONTROL (LQRIFC)
The LQR integrated fuzzy control utilizes both advantages from the LQR
controller and fuzzy logic controller as LQR controller can easily satisfies the
flying qualities and pilot rating requirements and fuzzy control can cope with the
nonlinearity of the system introducing a smart way to modifying the output gains
according to the actual performance blending the dynamic response that
generating better performance than using LQR alone. Fig. 4 describes the LQR
integrated fuzzy control (LQRIFC) for pitch controller. The system dynamics is
evaluated by LQR design process at each trimmed point for pitch control, in the
5. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 5
same manner it is possible to introduce the same procedure for lateral-directional
control Fig. 5. Eventually the LQR closed loop system poles can easily satisfy the
flying qualities specifications such as the damping ratio and the natural
frequencies which is the main requirement in designing closed loop aircraft
control system [4].
The states and output of the plant plus the compensator for both pitch and lateral
motions are
[ ]T
Fepitch qx εαδα= , [ ]T
Fpitch qy εα=
[ ]T
wralateral xrpx εδδφβ= , [ ]T
rlateral epey φε=
GrBuAxx ++=•
(3)
FrCxy += (4)
HxZ = (5)
Kyu −= (6)
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
−
−
−=
0002958.570
010000.10
002.2000
00
~~~
00
~~~
eqqqq
eq
BAA
BAA
A
δα
αδααα
, , ,
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
0
0
2.20
0
0
B
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
1
0
0
0
0
G
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
=
0
0
0
F
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
=
10000
0002958.570
02958.57000
C , [ ]0002958.570=H , [ ]lq KKKKyu α−=−=
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
−
−
−
−
=
00000010
01002958.57000
002.2000000
0002.200000
00
~~~~~~
00
~~~~~~
00
~~~~~~
00
~~~~~~
rrarrrprrr
rpaprppppp
rarp
rarp
BBAAAA
BBAAAA
BBAAAA
BBAAAA
A δδϕβ
δδϕβ
ϕδϕδϕϕϕϕβϕ
βδβδββϕβββ
, ,
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
00
00
2.200
02.20
00
00
00
00
B
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
01
00
00
00
00
00
00
00
G
Hxx
r
z
w
=⎥
⎦
⎤
⎢
⎣
⎡
−
=⎥
⎦
⎤
⎢
⎣
⎡
=
01002958.57000
00000010ϕ
6. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 6
]
c
r
FrCx
e
p
e
y +=
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎣
⎡∈
=
ϕ
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎣
⎡
−
−
=
00000010
00000100
00002958.57000
10000000
C
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎣
⎡
=
01
00
10
00
F
The control input may be expressed as[ T
ra uuu = Kyu −=
with ⎥
⎦
⎤
⎢
⎣
⎡
=
000
0
2
431
k
kkk
K
6. APPLICATION METHODOLOGY FOR AERIAL REFUELING INTEGRATED
CONTROL SYSTEM
The refueling procedure requires the tanker to fly straight and level at a constant
velocity. The receiving aircraft then closes in and moves to a standard position
behind and below the tanker boom. The two aircraft continue to fly in this
formation while the boom operator in the tanker's tail uses a joystick to move the
boom into position just above the receiver of the plane to be refueled. The
operator then extends the telescoping component of the main boom until the
nozzle is inserted into the receiver. This can be done automatically using some
kind of autopilot consists of three controllers one for pitch control, the second for
lateral control and the third for controlling the aircraft speed. Both controllers
proposed for pitch and lateral control will apply the LQR fuzzy control integration
and the other speed controller uses only fuzzy logic controller 14 rule-base
Mamdani type. The input references for both pitch and lateral controllers will be
fed by the tanker location on the head up display inside the cockpit. The input
reference for the speed controllers will be fed by the line of sight distance
between the aircraft and the tanker. For simulation purposes it is required to map
the tanker position from the earth fixed frame of reference to the aircraft wing
coordinates and this can be done by the proposed transformation as shown in
Fig. 6. Implementing the whole integrated aircraft control system on MATLAB/
SIMULINK thus calculating the actual trajectories and relative distance between
the aircraft and the tanker as shown in Fig. 7. Practically the relative distances
can be calculated by the Head Up display or GPS information that mounted on
both tanker and the aircraft connected to each other through UHF channels .
The following equations explain the transformation procedure starting from the
tanker position with respect to fixed frame of reference to wing coordinate of the
receiving aircraft with initializing small perturbed step (0.0001) to avoid the
singularities during simulation calculation.
X = Tanker X component relative to the fixed frame of reference
7. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 7
Y = Tanker Y component relative to the fixed frame of reference
Z = Tanker Z component relative to the fixed frame of reference
XF = Fighter X component relative to the fixed frame of reference
YF = Fighter Y component relative to the fixed frame of reference
ZF = Fighter Z component relative to the fixed frame of reference
XBO = Tanker X component relative to aircraft body axes at the fixed frame of
reference
YBO = Tanker Y component relative to aircraft body axes at the fixed frame of
reference
ZBO = Tanker Z component relative to aircraft body axes at the fixed frame of
reference
XB = Tanker X component relative to aircraft body axes
YB = Tanker Y component relative to aircraft body axes
ZB = Tanker Z component relative to aircraft body axes
θ , Ф, ψ = Rotation around X,Y, Z axes
A = cos θ cos ψ
B = (sin Ф sin θ cos ψ – cos Ф sin ψ)
C = (cos Ф sin θ cos ψ+ sin Ф sin ψ)
D = cos θ sin ψ
E = (sin Ф sin θ sin ψ + cos Ф cos ψ)
F = (cos Ф sin θ sin ψ – sin Ф cos ψ)
G = – sin θ
M = sin Ф cos θ
N = cos Ф cos θ
)])(())([(
)])(())([(
BDEANACGMABGCDFA
BDEAZAXGMABGXDYA
Z BO
−−−−−
−−−−−
= (7)
)(
)]()[(
BDEA
CDFAZXDYA
Y BO
BO
−
−−−
= (8)
A
CZBYX
X BOBO
BO
)( −−
= (9)
)])(())([(
)])(())([(
BDEANACGMABGCDFA
BDEAAZGXMABGDXAY
Z FFFF
SHIFT
−−−−−
−−−−−
= (10)
)(
)]()[(
BDEA
CDFAZDXAY
Y SHIFTFF
SHIFT
−
−−−
= (11)
A
CZBYX
X SHIFTSHIFTF
SHIFT
)( −−
= (12)
XB = XBO – X shift (13)
YB = YBO – Y shift (14)
ZB = ZBO – Z shift (15)
Fig. 8 shows all the control efforts of the control surfaces and the aircraft engine
power during the whole mission starting from the start point as in Fig. 7. until to
8. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 8
the point of contact to the tanker which is the most essential interval in the
mission. The alignment terminal control secures the position of the receiving
aircraft beneath the tanker of about 30 (ft) and the steady flight speed is equal
the same as the tanker flight speed. The figures show also the relative speed and
distances between the receiving aircraft and the tanker.
7. CONCLUSION
It is clear that designing aircraft controllers using the integration of both fuzzy
logic and LQR has a great benefit in tuning the output performance of the aircraft
particularly in aerial refueling systems. As the designing such autopilot requires
high precision in controlling the receiving aircraft to a certain lower point under
the flying tankers. The control strategy used will be divided into 3 phases, first
phase is the stability system augmentation stabilizing the receiving aircraft at
initial steady state flight. The second phase is the tracking phase controlling the
receiving aircraft from the starting point to the 1000 (ft) behind the tanker at the
desired lower point which is straight and lower from the tanker with 30 (ft) at this
phase it is clear that the receiving aircraft speed profile maintained at almost
constant speed as long as the receiving aircraft is away from the tanker then
decelerating with different acceleration rates till starting the next phase, actually
the smart fuzzy logic speed controller provide such profile according to the rule
bases that was previously discussed. The third phase will switch the control to
alignment controller which aligns the receiving aircraft with the center line of the
tanker with steady level flight decelerating the speed to reach the tanker speed at
the point of contact. Mean while the fuel boom will be extended down manually
by using joystick until connecting the receiving valve in the upper surface of the
receiving aircraft starting the refueling process. As shown in the previous figures
the control strategy satisfies all the requirements stated for aerial refueling
process such as flying qualities and the minimum estimated time (356 seconds)
for initial relative distances of (38000 ft) with application of a DRYDEN gust
model as a vertical gust . The previous figures show the effectiveness of using
such integration to cope with the applied disturbance more than using LQR
alone.
REFERENCES
[1] Stevens, B. L., Lewis, F.L., & Al-Sunni, F. (1991). Aircraft flight controls
design using output feedback. Journal of Guidance, Control, and Dynamics.
[2] Sugeno M. and Yasukawa T.,”A fuzzy-logic-based approach to qualitative
modeling,” IEEE Trans. Fuzzy Syst., vol. 1, pp. 7-31, 1993.
[3] Mendel J. M. and Mouzouris G. C.,”Designing fuzzy logic systems,” IEEE
Trans.Circuits Syst., vol. 44, pp. 885-895, Nov. 1997.
[4] Flying Qualities of Piloted Airplanes, MIL-F-8785C, 5 Nov. 1980.
9. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 9
[5] M.L. Fravolini, A. Ficola, M. R. Napolitano, G. Campa, M. G.
Perhinschi ”Development of Modeling and Control Tools for Aerial Refueling for
UAVs” Perugia University, 06100 Perugia, Ital,2000
Fig. 1. The structure of a Fuzzy Logic Control System
Fig. 2. Mamdani type fuzzy logic speed controller
Fig. 3. PID fuzzy logic controller output gains
10. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 10
Fig. 4. LQR integrated fuzzy control (LQRIFC) for pitch controller
Fig. 5. LQR integrated fuzzy control (LQRIFC) for lateral-directional controller
Fig. 6. Tanker position transformation to aircraft wing axes
11. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 11
Fig. 7. Actual trajectories for tanker and receiving aircraft
12. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-04 12
Fig. 8. F-16 nonlinear model performance