• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.191-193
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• 2005

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. To increase the robustness, fixed gam PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.962-966
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• 1996

A conventional PI controller does not provide a proper response in face of various kinds of load variation. In this paper, three types of fuzzy-PI hybrid control scheme are proposed in order to improve the performance of the PI controller. The proposed control schemes are applied to the speed controller of AC servo motor systems. The effectiveness of the proposed methods is shown by computer simulation and the advantage of each control scheme is discussed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.352-357
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• 2000

The vector control scheme is usually applied to the high performance induction motor drives. The PI controller is adopted traditionally to control the motor speed and currents in the vector control scheme. In this case, the dynamic performance of the induction motor is dependent on the PI gains and the gain optimization is necessary in order to get a good dynamic performance. But, it is very hard to optimize the PI gains uniquely within the speed control range because the equivalent model of the motor control system should be known exactly. In this paper, we propose the hybrid control scheme to remove the defects of PI controller. The hybrid control scheme includes the simplified fuzzy controller which operates in the transient state and the PI controller which operates in the steady state. The proposed scheme is applied to the vector control for induction motor, and the digital simulation and the experimental results are given to verify the proposed 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.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1400-1407
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• 2015

In the paper, we suggest bettered EHMECS(Enhanced Hybrid Multi Electrical Cupping System) to regulate automatically vacuum pressure using many cupping cup at once. We controlled accurately the pressure using S-PI control technique in pump motor to input the air inside cupping cup. S-PI control compared constant velocity, load and velocity variance between existing PI and FLC(Fuzzy Logic Control). The stabilization time of suggested S-PI control improve 20% of existing PI and 8% of FLC. The error constant of normal condition improved 71% of existing PI and 62% of FLC in steady speed and 80% of existing PI and 67% of FLC in load change. Also the error constant about velocity variance improve 45% of PI control. It is prove the suggested S-PI control technique. When use long time vacuum pressure of cupping cup regulated the suggested S-PI control technique, can loosen knotted muscles.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.4-101
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• 2002

I. Introduction ▶The PID(Proportional-Integral-Derivative) controller is widely used in the industry it can be implemented easily for a typical second order plant. ▶The parameters of PID controller should be adapted complicatedly if a plant is various or the load is present. ▶For solving the problem, many control techniques have been developed. ▶A major method is a hybrid Fuzzy-PID controller. But, in case of using this method, we can not obtain characteristic of rapidly response and not achieved compensation on disturbance. ▶Therefore, we will use compensator fuzzy controller a front Hybrid type fuzzy-PID controller...

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.31-41
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• 1993

In this paper, a fuzzy adaptive controller is proposed for the process with large delay time and unmodelled dynamics. The fuzzy adaptive controller consists of self tuning controller and fuzzy tuning part. The self tuning controller is designed with the continuous time GMV (generalized minimum variance) using emulator and weighted least square method. It is realized by the hybrid method. The controller has robust characteristics by adapting the inference rule in design parameters. The inference processing is tuned according to the operating point of the process having the nonlinear characteristics considering the practical application. We review the characteristics of the fuzzy adaptive controller through the simulation. The controller is applied to practical electric furnace. As a result, the fuzzy adaptive controller shows the better characteristics than the simple numeric self tuning controller and the PI controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.57-66
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper proposes hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme, The validity of the proposed controller is verified by results at different dynamic operating conditions.