• Journal of Power System Engineering
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• v.5 no.3
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• pp.104-113
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• 2001

This paper describes a precise position synchronous control of two axes rotating system using BLDC motors and a cooperative control based on decoupling technique and PI control law. The system is required performances both good speed following and minimum position synchronous errors simultaneously. To accomplish these goals, the three kinds of controllers are designed. At first, the current and speed controller are designed very simply to compensate the influences of disturbances and to follow up speed references quickly. Especially, the two degree of freedom PI controller is used considering both good tracking for speed reference input and quick rejection of disturbances in speed controller. Finally, a position synchronous controller is designed as a simple proportional controller to minimize position synchronous errors. The validity of the proposed method is confirmed through some numerical simulations. Moreover, the results are compared to the conventional master-slave control ones to show the effectiveness of the proposed system.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.110-114
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. In this paper maximum torque control of IPMSM drive using artificial intelligent(AI) controller is proposed. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using adaptive learning mechanism fuzzy neural network(ALM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the experimental results to verify the effectiveness of AI controller.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.312-314
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• 2006

This paper describes performance of the modified gain scheduling controller by speed control of a DC motor. The modified gain scheduling controller can perform tracking at more than one equilibrium points. The modified gain scheduling controller which considers transient response according to added zero shows better result of tracking performance than the unmodified gain scheduling controller shows.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1E
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• pp.16-22
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• 2009

In this paper, the new robust active noise controller was proposed to be applied for attenuating the noises when the nonlinear distortion in the secondary path exists. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional LMS controller and proposed controller, to be applied for actively controlling the noises and linearizing the nonlinear distortion in the secondary path. Also, the simulations results demonstrated that the proposed controller may have faster convergence speed and better capability of controlling the noises and compensating the nonlinear distortion than the conventional LMS controller.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1137-1139
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• 2002

In this paper, recurrent artificial neural network (RNN) based self tuning speed controller is proposed for the high performance drives of induction motor. RNN provides a nonlinear modeling of motor drive system and could give the information of the load variation, system noise and parameter variation of induction motor to the controller through the on-line estimated weights of corresponding RNN. Thus, proposed self tuning controller can change gains of the controller according to system conditions. The gain is composed with the weights of RNN. For the on-line estimation of the weights of RNN, extended kalman filter (EKF) algorithm is used. Self tuning controller that is adequate for the speed control of induction motor is designed. The availability of the proposed controller is verified through the MATLAB simulation with the comparison of conventional PI controller.

• Journal of the Korean Society of Safety
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• v.14 no.4
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• pp.108-113
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• 1999

This paper presents a study on fuzzy speed and flux controller used in a vector control of a CRPWM(Current Ragulated PWM) induction motor drive. In this paper, an approach for an easier design of the fuzzy controller is presented in order to obtain the desired value for the response time with minimal overshoot and to improve the steady state performance for speed step commands. The fuzzy controller is constructed only upon the knowledge of the motor behaviour and the desired speed response, and provides fast and robust control by reducing the effects of nonlinearities, parameter changes and load disturbance. The results of applying the fuzzy logic controller to an IM drive system are compared with those obtained by application of a conventional PI controller. The fuzzy controller provided a better response than the PI controller.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.97-102
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• 2003

In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation system noise, and parameter variation of the induction motor through the on-line estimated weights of the corresponding RNN. Thus, the proposed self-tuning controller can change the gains of the controller according to system conditions. The gain is composed with the weights of the RNN. For the on-line estimation of the RNN weights, an extended Kalman filter (EKF) algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor The availability of the proposed controller is verified through MATLAB simulations and is compared with the conventional PI controller.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.224-227
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• 2002

This paper is proposed new fuzzy controller for speed control of induction motor drive. New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. Proposed controller fuzzily clear out integrated quantifies according to situation. This paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.177-181
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• 2004

In this paper design of speed controller for AC servo system by rapid design system(RG-01D) using DSP of Realgain company is introduced. 'AC Servo-Designer' system, including CEMTool/SIMTool S/W, RG-DSPIO board, AC servo driver and AUTOTool program, is used in this research. Because 'AC Servo-Designer' system can use SIMTool blocks to design and implement various controller in short time, speed controller for AC servo system is easily designed and implemented according to control objectives.