• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1700-1707
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• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.10
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• pp.587-594
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• 2005

An adaptive observer for rotor resistance is designed to estimate rotor flux for the a-b model of an induction motor assuming that rotor speed and stator currents are measurable. A singularly perturbed model of the motor is used to design an Adaptive sliding mode observer which drives the estimated stator currents to their true values in the fast time scale. The adaptive observer on the sliding surface is based on the equivalent switching vector and both the estimated fluxes and the estimated rotor resistance converge to their true values. A speed controller considering the effects of parameter variations and external disturbance is proposed in this paper. First, induction motor dynamic model at nominal case is estimated. based on the estimated model, speed controller is designed to match the prescribed speed tracking specifications. Then a dead-time compensator and a robust controller are designed to reduce the effects of parameter variations and external disturbances. the desired speed tracking control performance can be preserved under wide operating range, and good speed load regulating performance. Some simulated results are provided to demonstrate the effectiveness of the Proposed controller.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2765-2768
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• 2003

The PI controller has many trial-and-error steps for gain design. This paper proposes a new design concept. In this method, a degree of stability and Kharitonov theory are applied and the controller gain is directly expressed by system parameters and current controller's bandwidth. Simulation results for permanent magnetic synchronous motor(PMSM) driving systems confirm the validity of proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.767-770
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• 1996

A H$\_$.inf./ contro theory was applied to motor speed control of two-mass system to get controller which acts effectively with control object including uncertainties. The H$\_$.inf./ control problem was composed and solved. After that, numerical simulation were executed to confirm ability of the controller which compared with PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2557-2561
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• 2005

The PID controller design and choosing PID parameters according to system response are proposed in this paper. Here PID controller is employed to control DC motor speed and Matlab program is used for calculation and simulation. Choosing PID parameters are demonstrated by several contrast experiments and a way for setting PID parameters values is discussed.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.200-203
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• 1998

In this paper, it deals with Switched Reluctance Motor(SRM) which has fuzzy logic contoroller(FLC). The modeling and FLC of SRM are presented. The modeling and FLC of SRM are presented. The results of simulation show the speed responce characteristics of SRM with FLC. As a result, the SRM controller with FLC is verified by comparison between PI controller and fuzzy logic controller.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.239-240
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• 2007

In this paper, a robust adaptive backstepping controller will be proposed for the speed control of permanent magnet synchronous motors in using electrical vehicles. Stator resistance, damping coefficient, load torque are considered as uncertainties and noise generated at applying load torque to motor is also considered. It shows that the backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the Proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.2
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• pp.94-99
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• 2004

In this paper, We design a RF control system capable of handling multiple POS thermal printers. The system has three parts including embedded master controller, RF controller and high-speed thermal printer. Specially the designed linux embedded controller has simple structure and high performance to connect the TCP/IP network. The effectiveness of the developed RF control system is shown by proposed food ordering system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1289-1301
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• 2011

In this paper, flux estimation method at the Induction motor is applied to stability flux estimate of possibility in overall speed domain. angle operation has voltage and current and speed information using the Induction motor direct control method. Induction motor direct control is material to flux information. Exact flux estimation method to using current model flux estimator of low-speed domain and voltage model flux estimator of high-speed domain. Speed and current and flux controller using PI controller. And error of integral requital for add to Anti-Windup PI controller. Verified to performance of Current model Flux controller and voltage model flux controller using Matlab / Simulink. Analysis has parameter influence of direct vector control and indirect vector control at the Induction motor vector control. So, verified to minute control. Analyzed to simulation result and proof to validity of presented algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.313-318
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• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive fuzzy neural network controller and artificial neural network(ANN). This control method is applicable over the entire speed range which 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 Adaptive-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper reposes speed control of IPMSM using Adaptive-FNN and estimation of speed using 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 a lied to IPMSM drive system controlled Adaptive-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the Adaptive-FNN and ANN controller.