• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.6-10
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• 1996

This paper presents an overview of research results obtained by the authors in a series of publications. Methods are developed both for time-varying and time-invariant for linear and nonlinear. for time domain and frequency domain . and for discrete-time and continuous-time systems. Among the topics presented are: 1. Learning control based on integral control concepts applied in the repetition domain. 2. New algorithms that give improved transient response of the indirect adaptive control ideas. 4. Direct model reference learning control. 5 . Learning control based frequency domain. 6. Use of neural networks in learning control. 7. Decentralized learning controllers. These learning algorithms apply to robot control. The decentralized learning control laws are important in such applications becaused of the usual robot decentralized controller structured.

• KIEAE Journal
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• v.14 no.4
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• pp.111-117
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• 2014

In South Korea, the government has recently enforced regulations associated with buildings. Temperature restriction in indoor environment is one of the common ways of energy reduction in order not to dissipate heating and cooling energy; however the people who are in restricted temperature feels uncomfortable. Furthermore, occupants cannot feel the same thermal sensation even they are in the same place. For the reason, occupants should express their thermal sensation and HVAC system should be able to apply their demand. It is proved by an adaptive principle. The adaptive model means that people react in ways which tend to restore their comfort, when change occurs such as to produce discomfort. In order to design HVAC control strategies based on adaptive model, we designated an existing office building as a reference building to gather data from actual field. Furthermore, we gathered occupants' thermal sensation and clothing insulation in real-time. We filtered the data with Kalman's filter method. The data was reasonable when there is an alarm messages for asking questionnaire. The response ratio were different in occupants' thermal condition. In conclusion, the filtered occupants' thermal sensation can be used as a real time HVAC control and input value of HVAC control.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.1-12
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• 1999

A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.33-40
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• 2009

This paper presents the high performance control of interior permanent magnet synchronous motor(IPMSM) using space vector(SV) PWM method based on hybrid artificial intelligent(HAI) controller. The HAI controller combines the advantages between adaptive fuzzy control and neural network The SV PWM method is applied to a speed control system of motor in the industry field until now and is feasible to improve harmonic rate of output current, switching frequency and response characteristics. This HAI controller is used instead of conventional PI controller in order to solve problems happening when calculating a reference voltage. The HAI controller improves speed performance by hybrid combination of reference model-based adaptive mechanism method, fuzzy control and neural network. This paper analyzes response characteristics of parameter variation, steady-state and transient-state using proposed HAI controller and this controller compares with conventional fuzzy neural network(FNN) and PI controller. Also, this paper proves validity of HAI controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.279-287
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• 2010

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. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning controller(AFLC). In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC. Also, this paper proposes speed control of IPMSM using AFLC1, current control of AFLC2 and AFLC3, and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled AFLC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.13-16
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• 1996

A new instantaneous torque control technique is presented for a high performance control of a permanent magnet synchronous motor. Using the model reference adaptive system technique, the linkage flux of the motor is estimated and the torque is instantaneously controlled by the proposed torque controller combining with a variable structure control and space vector PWM. The proposed torque control provides the advantage of reducing the torque pulsation caused by the flux harmonics. This control strategy is applied to the high torque PM synchronous motor drives for direct drive systems and is implemented by using a software of the DSP TMS320C30. The experiments are carried out for this system and the results well demonstrate the effectiveness of the proposed control.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.149-155
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• 1997

본 논문에서는 비선형 시변 시스템을 제어할 경우 제어시스템의 안정성을 보장하고 성능을 향상시키기 위한 새로운 적응제어 구조를 전개하였다. 주어진 플랜트가 선형 시불변이라는 가정하에 표준 기준 모델 적응제어기가 적용될 경우 발생되는 출력오차는 플랜트의 비선형 시변특성으로 인하여 점근적으로 0에 수렴되지 않는다. 이때 미지의 출력오차를 점근적으로 0에 수렴시키는 방법으로 퍼지보상기를 사용하였으며 결과적으로 플랜트의 비선형 시변 특성을 보상하는 효과를 얻을 수 있었다. 퍼지 보상기로는 출력오차등의 조건에 따라 이득이 변하는 퍼지 PID 보상기를 도입하여 안정하게 설계되도록 노력하였다. 또한 출력오차를 점근적으로 0에 수렴시키는 것은 표준 기준 모델 적응제어기 내부의 모든 파라미터와 신호가 유한하게 됨을 의미하기 때문에, 제어시스템 전체의 안정도를 보장할 뿐만 아니라 결과적으로 과도응답 성능을 향상시킬 수 있게 되었다. 몇가지 예제를 대상으로 시뮬레이션을 수행하고 그 결과를 분석함으로써 비선형 시변 시스템을 제어할 경우 본 논문에서 전개된 새로운 적응제어 구조의 타당성을 확인하였다.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.148-151
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• 1991

This paper describes the vector control system estimates rotor speed based on MRAS(Model Reference Adaptive Control) and this estimate is used for speed feedback control. The stability of speed estimator is proved on the basis of hyperstability theory. In order to improve the performance of speed control, the load torque is estimated by load torque observer and speed controller compensates this estimate value. Thus the robust vector control system against load torque disturbance is constructed.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.76-79
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• 1988

The sliding mode control in an effective method to eatablish robustness against parameter variation and disturbance. But. In sliding mode strategy, the control function is discontinuous on the hyperplane. However the discontinuous change in control structure caves the controller input to chaffer and gives non-zero steady state error. Consequently, a multiloop feedback control system supplemented by a complelmentary controller is used to improved the drive performence of a DC servo motor and reduce sensitivity to parameter variation, nonlinear effects, and other disturbances.