EPE Association: EPE 1997 â€“ 35: Dialogue Session DS4b-2: FUZZY CONTROL

EPE 1997 â€“ 35: Dialogue Session DS4b-2: FUZZY CONTROL
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 1997 - Conference > EPE 1997 â€“ 35: Dialogue Session DS4b-2: FUZZY CONTROL

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   CONTROL OF A THREE-PHASE PWM FRONT END RECTIFIER USING FUZZY LOGIC
By J. Rodriguez; J. Hernandez; M. Salgado; F. Liebe [View]
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Abstract: This paper proposes the use of a fuzzy logic controller, to control the output D.C. voltage of a three-phase Active Front End (AFE) rectifier. This converter uses 6 power transistors with their respective antiparalel diodes to generate practically sinusoidal input currents. The perfonnance of the fuzzy logic controller is compared with that of the classical proportional-integral (PI) controller used usually in this type of converters. The results of this work show that the fuzzy logic controller is more than 10 times faster than the classical PI controller, in response to a load perturbation.

   COMPARISON BETWEEN FUZZY AND CLASSICAL SPEED CONTROL WITIDN A FIELD ORIENTED METHOD FOR INDUCTION MOTORS
By L. Baghli; H. Razik; A. Rezzoug [View]
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Abstract: In this paper, we present a rotor field oriented method for induction motors, paying special attention to the speed control loop. We compare the performances of a fuzzy controller to the ones of an lP anti windup controller in an internal loop. Experimental results on position control and speed control under load are presented and commented.

   TMS320 DSP IMPLEMENTATION OF FUZZY-NEURAL CONTROLLED INDUCTION MOTOR DRIVES
By S. Beierke; P. Vas; A.-F. Stronach [View]
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Abstract: The digital implementation of fuzzy-neural-controllers in induction motor drives, using TMS320 DSPs is discussed. Two types of induction motor drive are discussed - a drive with scalar speed control and also a vector drive. In the scalar drive, the machine is supplied by a current controlled PWM inverter. In one version of the drive, a fuzzy-neural controller outputs the reference value of the modulus of the stator current vector and in a second version, there is also an additional fuzzy-neural speed controller. In the vector drive, . the speed controller is a fuzzy-neural controller and the machine is supplied by PWM voltagesource inverter. The design of these fuzzy-neural controllers is also discussed. Experimental results are also given and the advantages of the fuzzy-neural approach are emphasised.

   FUZZY LOGIC AS CONTROL METHOD FOR POWER ELECTRONICS CONVERTERS
By A.-P. Martins; A.-S. Carvalho [View]
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Abstract: This paper presents an application based on Fuzzy Logic Controllers (FLC) in the parallel operation of inverters inside Uninterruptible Power Supply Systems (UPS). It is described, in a simplified way, the parallel operation of UPSs in order to show its MultiInput/ Multi-Output (MIMO) characteristic, with high cross coupling between inputs and outputs. The system high order turns it complex to analyze in terms of transfer functions and difficult to model, due to the imprecision in some parameters. The most usual control methods are described and it is justified the implementation of a MIMO fuzzy controller. Simulation and experimental results for two controller types are presented.

   FUZZY INVERSION BASED ON PIECEWISE LINEARIZATION AND RULE BASE REDUCTION
By P. Baranyi; P. Korondi; H. Hashimoto [View]
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Abstract: This paper proposes a new design method based on linguistic model inversion and fuzzy rule reduction using singular value decomposition. Firstly, a piecewise linear fuzzy approximation of the controlled plant is identified by measurement. Secondly, the linear cells of the fuzzy model is inverted to achieve a controller. The inversion increases the fuzzy rule base. Thirdly, the redundant or small weighted information are removed from the fuzzy rule base. Experimental results of a transputer controlled single-degree-of-freedom motion control system are presented. The experimental system consists of a conventional DC servo gear motor with encoder feedback and variable inertia load coupled by a relatively rigid shaft.

   SPEED AND POSITON CONTROL OF BRUSHLESS DC MACHINES EMPLOYING NEURAL NETWORKS
By J. J. Reimondez; M. I. Gimenez; V. M. Guzman; R. Moncada; J. A. Restrepo [View]
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Abstract: On this work, different alternatives using Neural Networks for controlling speed and position in brushless DC machines are studied. Neural Networks are used to implement three control strategies: Direct identification of the plant, identification of the inverse plant and copy of an existing controller. This work compares the efficiency and speed of each of these strategies, to create the basis for more complex studies of Neural Networks used in Power Electronics Systems.

   A CLOSED-FORM APPROACH TO THE DESIGN OF FUZZY-PI CONTROLLER
By A. Monti; A. Scaglia [View]
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Abstract: The paper presents a new approach to the application of fuzzy logic to electrical drives control. An analytical methodology aimed to define fuzzy controllers which show features similar to standard industrial ones, is reported. The new regulator performances are completely overlapped to classical PI ones in small signal region; but the performances are improved in the large signal operation, thanks to the non linear fuzzy logic features. The analytical theory is then verified by simulation and on a laboratory DC drive system.

   APPLICATION OF NOVEL FUZZY CONTROLLERS FOR A POSITION SERVO SYSTEM WITH AN INDUCTION MACHINE
By Z. Wu; D. Naunin [View]
[Download]

Abstract: Thispaper presents the application of fuzzy controllers for position and current regulation in a field-oriented controlled induction motor for a position servo system. The design method of the fuzzy controller for current regulation is new. It provides a scheme for the incorporation of heuristics and mathematical models and combines the fuzzy logic and linear multiple variable control technique. The experimental implementation of the fuzzy controllers is carried out with an intelÂ® 486 processor system. The performance of the fuzzy controllers is compared experimentally with that of conventional PI controllers. The test results verity that the fuzzy controller has high robustness and high dynamic performance.

EPE 1997 â€“ 35: Dialogue Session DS4b-2: FUZZY CONTROL
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 1997 - Conference > EPE 1997 â€“ 35: Dialogue Session DS4b-2: FUZZY CONTROL
	[return to parent folder]

	CONTROL OF A THREE-PHASE PWM FRONT END RECTIFIER USING FUZZY LOGIC By J. Rodriguez; J. Hernandez; M. Salgado; F. Liebe	[View] [Download]
Abstract: This paper proposes the use of a fuzzy logic controller, to control the output D.C. voltage of a three-phase Active Front End (AFE) rectifier. This converter uses 6 power transistors with their respective antiparalel diodes to generate practically sinusoidal input currents. The perfonnance of the fuzzy logic controller is compared with that of the classical proportional-integral (PI) controller used usually in this type of converters. The results of this work show that the fuzzy logic controller is more than 10 times faster than the classical PI controller, in response to a load perturbation.

	COMPARISON BETWEEN FUZZY AND CLASSICAL SPEED CONTROL WITIDN A FIELD ORIENTED METHOD FOR INDUCTION MOTORS By L. Baghli; H. Razik; A. Rezzoug	[View] [Download]
Abstract: In this paper, we present a rotor field oriented method for induction motors, paying special attention to the speed control loop. We compare the performances of a fuzzy controller to the ones of an lP anti windup controller in an internal loop. Experimental results on position control and speed control under load are presented and commented.

	TMS320 DSP IMPLEMENTATION OF FUZZY-NEURAL CONTROLLED INDUCTION MOTOR DRIVES By S. Beierke; P. Vas; A.-F. Stronach	[View] [Download]
Abstract: The digital implementation of fuzzy-neural-controllers in induction motor drives, using TMS320 DSPs is discussed. Two types of induction motor drive are discussed - a drive with scalar speed control and also a vector drive. In the scalar drive, the machine is supplied by a current controlled PWM inverter. In one version of the drive, a fuzzy-neural controller outputs the reference value of the modulus of the stator current vector and in a second version, there is also an additional fuzzy-neural speed controller. In the vector drive, . the speed controller is a fuzzy-neural controller and the machine is supplied by PWM voltagesource inverter. The design of these fuzzy-neural controllers is also discussed. Experimental results are also given and the advantages of the fuzzy-neural approach are emphasised.

	FUZZY LOGIC AS CONTROL METHOD FOR POWER ELECTRONICS CONVERTERS By A.-P. Martins; A.-S. Carvalho	[View] [Download]
Abstract: This paper presents an application based on Fuzzy Logic Controllers (FLC) in the parallel operation of inverters inside Uninterruptible Power Supply Systems (UPS). It is described, in a simplified way, the parallel operation of UPSs in order to show its MultiInput/ Multi-Output (MIMO) characteristic, with high cross coupling between inputs and outputs. The system high order turns it complex to analyze in terms of transfer functions and difficult to model, due to the imprecision in some parameters. The most usual control methods are described and it is justified the implementation of a MIMO fuzzy controller. Simulation and experimental results for two controller types are presented.

	FUZZY INVERSION BASED ON PIECEWISE LINEARIZATION AND RULE BASE REDUCTION By P. Baranyi; P. Korondi; H. Hashimoto	[View] [Download]
Abstract: This paper proposes a new design method based on linguistic model inversion and fuzzy rule reduction using singular value decomposition. Firstly, a piecewise linear fuzzy approximation of the controlled plant is identified by measurement. Secondly, the linear cells of the fuzzy model is inverted to achieve a controller. The inversion increases the fuzzy rule base. Thirdly, the redundant or small weighted information are removed from the fuzzy rule base. Experimental results of a transputer controlled single-degree-of-freedom motion control system are presented. The experimental system consists of a conventional DC servo gear motor with encoder feedback and variable inertia load coupled by a relatively rigid shaft.

	SPEED AND POSITON CONTROL OF BRUSHLESS DC MACHINES EMPLOYING NEURAL NETWORKS By J. J. Reimondez; M. I. Gimenez; V. M. Guzman; R. Moncada; J. A. Restrepo	[View] [Download]
Abstract: On this work, different alternatives using Neural Networks for controlling speed and position in brushless DC machines are studied. Neural Networks are used to implement three control strategies: Direct identification of the plant, identification of the inverse plant and copy of an existing controller. This work compares the efficiency and speed of each of these strategies, to create the basis for more complex studies of Neural Networks used in Power Electronics Systems.

	A CLOSED-FORM APPROACH TO THE DESIGN OF FUZZY-PI CONTROLLER By A. Monti; A. Scaglia	[View] [Download]
Abstract: The paper presents a new approach to the application of fuzzy logic to electrical drives control. An analytical methodology aimed to define fuzzy controllers which show features similar to standard industrial ones, is reported. The new regulator performances are completely overlapped to classical PI ones in small signal region; but the performances are improved in the large signal operation, thanks to the non linear fuzzy logic features. The analytical theory is then verified by simulation and on a laboratory DC drive system.

	APPLICATION OF NOVEL FUZZY CONTROLLERS FOR A POSITION SERVO SYSTEM WITH AN INDUCTION MACHINE By Z. Wu; D. Naunin	[View] [Download]
Abstract: Thispaper presents the application of fuzzy controllers for position and current regulation in a field-oriented controlled induction motor for a position servo system. The design method of the fuzzy controller for current regulation is new. It provides a scheme for the incorporation of heuristics and mathematical models and combines the fuzzy logic and linear multiple variable control technique. The experimental implementation of the fuzzy controllers is carried out with an intelÂ® 486 processor system. The performance of the fuzzy controllers is compared experimentally with that of conventional PI controllers. The test results verity that the fuzzy controller has high robustness and high dynamic performance.