• 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.577-580
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• 1996

LQ-servo is a stability-robustness guaranteed multivariable controller design method based on the LQR structure to improve command following performance with output feedback. In this paper, a new type of PI controller based on LQ-servo is introduced. Then, Command following performance is improved using the limiting behavior of the control gain and weighting factors on the low frequency part of design parameter Q that is the state weighting matrix in the cost function.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.47-49
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• 2005

This paper presents a robust speed control method of induction motors(IM) using a Non-linear PI controller(NPI), NPI is high gain controller in region of small error, and low gain controller in region of large error. so in steady state, system will be robust against variation of load torque. The simulation and experiment results confirm the validity of proposed control scheme.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.227-231
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• 2006

This paper presents a robust speed control method of induction motors(IM) using a Non-linear PI controller(NPI). NPI is high gain controller in region of small error, and low gain controller in region of large error. So in steady state, system will be robust against variation of load torque. The simulation and experiment results confirm the validity of proposed control scheme.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.345-349
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• 2000

This paper presents an extended integral control with the PI controller by introducing the delay and decaying factors. The extended integral control scheme is developed by substituting the proportional convolution integral control for the PI(Proportional Integral) control. So far, the integral part of PI controller produces a signal that is proportional to the time integral of the input signal to the controller. The steady-state operation points are affected forever by errors in the past due to the input signal containing the information of the error in the past. These phenomena may cause some disturbances for other control purposes related to the given PI control. Introduction of forgetting factors to the error in the past can resolve the disturbance problems. Various forgetting factors are developed using the delay elements, the decaying factors, and the combination of the delay and decaying factors. The proposed various extended integral control schemes can be applicable to the corresponding PI control designs in which the error in the past may badly affect the current steady-state operation points and may cause some disturbances for other control purposes.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.488-493
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• 2008

A mathematical model of molten steel level for continuous casting process is presented, where the molten steel level, input and output flow in the mold, the relation between stopper position and input flow etc. are considered. The mathematical model is implemented and simulated by using MATLAB. Comparing the result of molten steel level from the simulator with that of real plant, the performance of the model is shown to be reasonable. By using this simulator, it is shown that PI controller with variable P gain, adjusted by fuzzy logic system, has better control result than conventional PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.613-618
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• 1992

We propose a new control architecture which consists of a PI controller and a neural network(NN) controller connected together in parallel. This architecture is well adapted to a wide range of uncertainties and variations of systems. The NN controller is learned through weights of the emulator which identify the dynamic chracteristics of the systems. A performance evaluation level of two NN's decides automatically which controller of the two controllers will be used mainly. The PI controller operates mainly during learning phase of the NN controller whereas a good performance is obtained from the NN controller only, when the NN controller is learned sufficiently.

• 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 Telematics and Electronics B
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• v.33B no.6
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• pp.12-22
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• 1996

A numerous designs of PI controllers have been suggested to solve out trade-off between tracing and regulating problems. We constructed the PI controller system with two-degree-of-freedom that is more analytic and a better approach to a practical one. In the conventional H$_{2}$ design of optimal PI controllers, the cost function includes only the plant output terms due to the divergent problems. Since the platn input temr is not considered in PI controller design, occasionally, the plant input thends to be either very large or saturated. To solve the prior mentioned problems, we employed a mixed $H_2/H_{\infty}$ method that combines the H$_{2}$ design method to decide optimal parameters of PI controller and the $H_2/H_{\infty}$ design method to minimize the maximum amplitude of plant input. The calculation time of the H$_{infty}$ norm was considerably reduced by the simple scalar function obtained by the wiener-hopf factorization of non-scalar functions.