EPE Association: EPE 2001 - Topic 04b: Fuzzy Control, Neuronal Control

EPE 2001 - Topic 04b: Fuzzy Control, Neuronal Control
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2001 - Conference > EPE 2001 - Topic 04: APPLICATION OF CONTROL METHODS TO ELECTRICAL SYSTEMS > EPE 2001 - Topic 04b: Fuzzy Control, Neuronal Control

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   A Fuzzy Logic-Based Load Frequency Controller:(The Multi-Area Control
By A. M. Abdel-Hamid [View]
[Download]

Abstract: This paper extends a research work of fuzzy logic control application for Load Frequency Control(LFC) of electric power system. A fuzzy logic algorithm is proposed to control an interconnected multi area power system. The advantage of the designed LFC controller is that its input signals can be taken centrally from the tie line power which straightforwardly measurable at any individual area. Accordingly, the high costs of local LFC at every station can be minimized. A throughout examination of the membership functions has been executed in order to get robust controller action even if the areas parameters are changing around more than ±50% uncertainty factors. Using the tie line power as an input to the fuzzy controller has proved that they include enough knowledge base to enable this controller giving efficient damping to the frequency variations allover the different interconnected buses.

   A solar battery charger for two modes of operation using a DC-DC buck
By R. M. Lamaison; S. Vivas; J. Peracaula [View]
[Download]

Abstract: In this paper a solar battery charger for two modes of operation using a dc-dc buck converter based on a Fuzzy Logic Controller (FLC) has been worked out. To improve energetic efficiency of a photovoltaic system an optimum power transfer from the solar panel to its load is needed. A C++ language program to simulate the system and the Fuzzy Logic Control in a closed loop scheme has been developed. On the other hand, experimental results of the FLC operating in two power modes of charges are presented. The two modes of charges are constant current with voltage limited and constant voltage with current limited.

   Comparison between fuzzy logic and sliding control applied to DC motor
By F. Betin; A. Sivert; D. Pinchon [View]
[Download]

Abstract: In this paper, two control strategies are used to control the position of a DC motor drive. The first one is based on the fuzzy logic theory and the second one is based on the variable structure approach. The designs of the two control laws are completely different but the aims of the two algorithms are the same. Indeed, when the parameters of the two controllers are correctly chosen, the trajectories in the phase plane slides around the same line. The characteristics of the two controllers are first presented and then the experimental results obtained with an Intel 80C196kb microcontroller are depicted.

   Control laws soft switching for a dc/dc converter
By D. Alejo; P. Maussion; J. Faucher [View]
[Download]

Abstract: This paper describes a new principle lying on soft commutation between two control laws by the mean of fuzzy logic used to design a robust and simple control law for a dc to dc converter. This soft switching between a classical IP controller and a simple non-linear law provides significant dynamic and static performances enhancement on simulation and experimental results. The tuning of the fuzzy logic parameters is made through Hooke and Jeaves optimisation procedure.

   Fuzzy Adaptive Control Methods for Power Electronics Applications
By A. P. Martins; A. S. Carvalho [View]
[Download]

Abstract: Fuzzy logic control application in power electronics is relatively new. However, the superior performance obtained in some cases originated high quality research in the difficult domains of controller adaptation and stability. General stability results, as in conventional control methods, are not easy to obtain and usually are associated with particular processes and controller structures. In the field of adaptive fuzzy control, there are much more quantitative and qualitative results. In this paper it is studied the application of fuzzy adaptive control methods in power electronics and systems. These applications are usually characterized by a known process structure but with some poor knowledge of its dynamics, parameters and disturbances. This is a major application area of fuzzy adaptive systems. In this paper it is discussed different adaptive fuzzy control methods applied to power electronics and systems and it is presented an illustrative example.

   Fuzzy logic application for variable speed wind turbines
By M.M. Prats; E. Galván; J.M. Carrasco; J..A. Sánchez; L.G. Franquelo; C. Batista [View]
[Download]

Abstract: This paper describes a fuzzy logic application for improving the variable speed and blade pitch wind turbine performance. The simulated model is going to be implemented using a programmable logic controller as the fuzzy controller designed. The used fuzzy controller as well as improving transition between power optimization and power limitation of the wind turbine at rated wind speed, it also permits to improve the captured wind energy at high wind speed working conditions using wind speed as input controller.

   Fuzzy Logic Control for Direct Torque Control Induction Motor Drives..
By Y-S. Lai; J-C. Lin [View]
[Download]

Abstract: Recent research results [1-3] have shown that using conventional PWM technique for inverter control instead of switching table in a Direct Torque Control (DTC) induction motor drive can effectively reduce the torque ripple without invoking the increase of sampling frequency. However, three controllers, including torque, flux and speed controllers, are required for DTC-based induction motor drives with PWM inverter control. Moreover, the parameters of controllers are usually decided by trial and error approach. The objective of this paper is to present the applications of fuzzy logic control to DTC-based induction motor drives with inverter controlled using space vector modulation technique. It will be shown that the controllers are implemented using PI-type fuzzy logic control and the presented DTCbased induction motor drive has the features of fast response, disturbance rejection, and low speed ripple. Experimental results derived from a test system will be presented confirming the theoretical development.

   Intelligent Battery Charger for Mobile Applications
By D.T.W. Liang; A. Sanchez T. [View]
[Download]

Abstract: An intelligent battery charger algorithm is presented using a fuzzy rule-based time interval method. The proposed strategy is capable of pre-determining the battery charge status prior to charging, and correctly terminating the charging process without overcharging the battery beyond its full capacity. The scheme is designed and implemented using a low-cost micro controller chip as the brain to control a prototype power transistor charger. Theoretical analysis are illustrated and explained. Experimental results are presented for verification.

   Investigations into the performance of various control methods for...
By Y-S. Lai; J-C. Lin [View]
[Download]

Abstract: The main theme of this paper is to investigate the performance of various types control methods, including proportional-integral (PI) control, PI-type fuzzy logic control (FLC), proportional-derivative (PD) type FLC, hybrid control, and combination of PD-type FLC and I control, for direct torque control (DTC) induction motor drives. The so-called hybrid control approach is a new method presented in this paper, which consists of PI control at steady state, PI-type fuzzy logic control at transient state, and a simple switching mechanism between steady and transient states. The pros and cons of these controllers will be demonstrated by intensive experimental results. It will be shown that the proposed hybrid control approach is with fast tracking capability, less steady state error, and robust to load disturbance while not resorting to complicated or observer-based control method.

   Neural network based predictive control of electrical drives
By I. Petrovic; Z. Rac; N. Peric [View]
[Download]

Abstract: A control strategy based on generalized predictive controller (GPC) is proposed for control of electrical drives with transmission elasticity and backlash. Neural network based model is used for identification of the two-mass mechanical system with elastic transmission and backlash with negligible friction. It is assumed that only measurement at the load side is available. Since GPC controller requires linear process model, neural model is linearized by means of instantaneous linearization in each sample instant. This control strategy is then compared to the classical GPC based on linear process model by computer simulations and experimentally on a laboratory model of the electrical drive with transmission elasticity and backlash.

   Neural Networks Implementation of MRAS in Induction Motor Drive
By J. Jelonkiewicz; A. Przyby³ [View]
[Download]

Abstract: In the paper four rotor speed estimators are considered, which are based on Model Reference Adaptive Systems (MRAS). Then neural networks structures are selected to implement the schemes. This approach offers more freedom to select better set of input signals for the networks at the cost of open loop operation. The best networks substituting reference model and adaptive model with controller are compared to select the best configuration. Then the networks are implemented in the DSP system It is expected that these networks can offer additional features like better accuracy and insensitivity to motor parameter variation.

   Neural Networks Rotor Position Estimators in PM synch. motor drive
By J. Jelonkiewicz [View]
[Download]

Abstract: In the paper different rotor position estimation methods without speed/position sensors, applied in PM synchronous motor (PMSM), are considered. Then neural networks are proposed to diminish computing requirements. It is expected that these networks can estimate rotor position with high accuracy and can offer other features like insensitivity to motor parameter variation.

   Speed-Sensorless Control Of An Induction Motor Using Fuzzy Logic
By D. Pirjan; F. Labrique; P. Sente [View]
[Download]

Abstract: The paper presents the experimental results obtained with a speed-sensorless FOC of an induction motor (IM) supplied by a PWM-Voltage Source Inverter (VSI). The speed tuning signal is estimated with a model reference adaptive system (MRAS) observer which uses the back e.m.fs quantities. Mamdani’s fuzzy logic controllers (FLC) are used for the speed controller and also for the MRAS controller.

EPE 2001 - Topic 04b: Fuzzy Control, Neuronal Control
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2001 - Conference > EPE 2001 - Topic 04: APPLICATION OF CONTROL METHODS TO ELECTRICAL SYSTEMS > EPE 2001 - Topic 04b: Fuzzy Control, Neuronal Control
	[return to parent folder]

	A Fuzzy Logic-Based Load Frequency Controller:(The Multi-Area Control By A. M. Abdel-Hamid	[View] [Download]
Abstract: This paper extends a research work of fuzzy logic control application for Load Frequency Control(LFC) of electric power system. A fuzzy logic algorithm is proposed to control an interconnected multi area power system. The advantage of the designed LFC controller is that its input signals can be taken centrally from the tie line power which straightforwardly measurable at any individual area. Accordingly, the high costs of local LFC at every station can be minimized. A throughout examination of the membership functions has been executed in order to get robust controller action even if the areas parameters are changing around more than ±50% uncertainty factors. Using the tie line power as an input to the fuzzy controller has proved that they include enough knowledge base to enable this controller giving efficient damping to the frequency variations allover the different interconnected buses.

	A solar battery charger for two modes of operation using a DC-DC buck By R. M. Lamaison; S. Vivas; J. Peracaula	[View] [Download]
Abstract: In this paper a solar battery charger for two modes of operation using a dc-dc buck converter based on a Fuzzy Logic Controller (FLC) has been worked out. To improve energetic efficiency of a photovoltaic system an optimum power transfer from the solar panel to its load is needed. A C++ language program to simulate the system and the Fuzzy Logic Control in a closed loop scheme has been developed. On the other hand, experimental results of the FLC operating in two power modes of charges are presented. The two modes of charges are constant current with voltage limited and constant voltage with current limited.

	Comparison between fuzzy logic and sliding control applied to DC motor By F. Betin; A. Sivert; D. Pinchon	[View] [Download]
Abstract: In this paper, two control strategies are used to control the position of a DC motor drive. The first one is based on the fuzzy logic theory and the second one is based on the variable structure approach. The designs of the two control laws are completely different but the aims of the two algorithms are the same. Indeed, when the parameters of the two controllers are correctly chosen, the trajectories in the phase plane slides around the same line. The characteristics of the two controllers are first presented and then the experimental results obtained with an Intel 80C196kb microcontroller are depicted.

	Control laws soft switching for a dc/dc converter By D. Alejo; P. Maussion; J. Faucher	[View] [Download]
Abstract: This paper describes a new principle lying on soft commutation between two control laws by the mean of fuzzy logic used to design a robust and simple control law for a dc to dc converter. This soft switching between a classical IP controller and a simple non-linear law provides significant dynamic and static performances enhancement on simulation and experimental results. The tuning of the fuzzy logic parameters is made through Hooke and Jeaves optimisation procedure.

	Fuzzy Adaptive Control Methods for Power Electronics Applications By A. P. Martins; A. S. Carvalho	[View] [Download]
Abstract: Fuzzy logic control application in power electronics is relatively new. However, the superior performance obtained in some cases originated high quality research in the difficult domains of controller adaptation and stability. General stability results, as in conventional control methods, are not easy to obtain and usually are associated with particular processes and controller structures. In the field of adaptive fuzzy control, there are much more quantitative and qualitative results. In this paper it is studied the application of fuzzy adaptive control methods in power electronics and systems. These applications are usually characterized by a known process structure but with some poor knowledge of its dynamics, parameters and disturbances. This is a major application area of fuzzy adaptive systems. In this paper it is discussed different adaptive fuzzy control methods applied to power electronics and systems and it is presented an illustrative example.

	Fuzzy logic application for variable speed wind turbines By M.M. Prats; E. Galván; J.M. Carrasco; J..A. Sánchez; L.G. Franquelo; C. Batista	[View] [Download]
Abstract: This paper describes a fuzzy logic application for improving the variable speed and blade pitch wind turbine performance. The simulated model is going to be implemented using a programmable logic controller as the fuzzy controller designed. The used fuzzy controller as well as improving transition between power optimization and power limitation of the wind turbine at rated wind speed, it also permits to improve the captured wind energy at high wind speed working conditions using wind speed as input controller.

	Fuzzy Logic Control for Direct Torque Control Induction Motor Drives.. By Y-S. Lai; J-C. Lin	[View] [Download]
Abstract: Recent research results [1-3] have shown that using conventional PWM technique for inverter control instead of switching table in a Direct Torque Control (DTC) induction motor drive can effectively reduce the torque ripple without invoking the increase of sampling frequency. However, three controllers, including torque, flux and speed controllers, are required for DTC-based induction motor drives with PWM inverter control. Moreover, the parameters of controllers are usually decided by trial and error approach. The objective of this paper is to present the applications of fuzzy logic control to DTC-based induction motor drives with inverter controlled using space vector modulation technique. It will be shown that the controllers are implemented using PI-type fuzzy logic control and the presented DTCbased induction motor drive has the features of fast response, disturbance rejection, and low speed ripple. Experimental results derived from a test system will be presented confirming the theoretical development.

	Intelligent Battery Charger for Mobile Applications By D.T.W. Liang; A. Sanchez T.	[View] [Download]
Abstract: An intelligent battery charger algorithm is presented using a fuzzy rule-based time interval method. The proposed strategy is capable of pre-determining the battery charge status prior to charging, and correctly terminating the charging process without overcharging the battery beyond its full capacity. The scheme is designed and implemented using a low-cost micro controller chip as the brain to control a prototype power transistor charger. Theoretical analysis are illustrated and explained. Experimental results are presented for verification.

	Investigations into the performance of various control methods for... By Y-S. Lai; J-C. Lin	[View] [Download]
Abstract: The main theme of this paper is to investigate the performance of various types control methods, including proportional-integral (PI) control, PI-type fuzzy logic control (FLC), proportional-derivative (PD) type FLC, hybrid control, and combination of PD-type FLC and I control, for direct torque control (DTC) induction motor drives. The so-called hybrid control approach is a new method presented in this paper, which consists of PI control at steady state, PI-type fuzzy logic control at transient state, and a simple switching mechanism between steady and transient states. The pros and cons of these controllers will be demonstrated by intensive experimental results. It will be shown that the proposed hybrid control approach is with fast tracking capability, less steady state error, and robust to load disturbance while not resorting to complicated or observer-based control method.

	Neural network based predictive control of electrical drives By I. Petrovic; Z. Rac; N. Peric	[View] [Download]
Abstract: A control strategy based on generalized predictive controller (GPC) is proposed for control of electrical drives with transmission elasticity and backlash. Neural network based model is used for identification of the two-mass mechanical system with elastic transmission and backlash with negligible friction. It is assumed that only measurement at the load side is available. Since GPC controller requires linear process model, neural model is linearized by means of instantaneous linearization in each sample instant. This control strategy is then compared to the classical GPC based on linear process model by computer simulations and experimentally on a laboratory model of the electrical drive with transmission elasticity and backlash.

	Neural Networks Implementation of MRAS in Induction Motor Drive By J. Jelonkiewicz; A. Przyby³	[View] [Download]
Abstract: In the paper four rotor speed estimators are considered, which are based on Model Reference Adaptive Systems (MRAS). Then neural networks structures are selected to implement the schemes. This approach offers more freedom to select better set of input signals for the networks at the cost of open loop operation. The best networks substituting reference model and adaptive model with controller are compared to select the best configuration. Then the networks are implemented in the DSP system It is expected that these networks can offer additional features like better accuracy and insensitivity to motor parameter variation.

	Neural Networks Rotor Position Estimators in PM synch. motor drive By J. Jelonkiewicz	[View] [Download]
Abstract: In the paper different rotor position estimation methods without speed/position sensors, applied in PM synchronous motor (PMSM), are considered. Then neural networks are proposed to diminish computing requirements. It is expected that these networks can estimate rotor position with high accuracy and can offer other features like insensitivity to motor parameter variation.

	Speed-Sensorless Control Of An Induction Motor Using Fuzzy Logic By D. Pirjan; F. Labrique; P. Sente	[View] [Download]
Abstract: The paper presents the experimental results obtained with a speed-sensorless FOC of an induction motor (IM) supplied by a PWM-Voltage Source Inverter (VSI). The speed tuning signal is estimated with a model reference adaptive system (MRAS) observer which uses the back e.m.fs quantities. Mamdani’s fuzzy logic controllers (FLC) are used for the speed controller and also for the MRAS controller.