• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.614-616
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• 2004

It is waste of time in industrial plant that the PI controller gain tuning. The PI controller has many trial-and-error steps for gain design. This paper proposes the optimum gain design of PI controller using a speed estimation in sensorless vector-control. In this method, a degree of stability and Hurwitz theory are applied and the controller gain is expressed by system parameters.

• Journal of Power System Engineering
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• v.18 no.5
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• pp.28-34
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• 2014

This paper deals with optimum PI controller design using genetic algorithm to improve control performance and robustness for an oil cooler system. The optimum PI gain was found to minimize an object function, integrated absolute error, and to satisfy control design specifications such as overshoot and settling time based on practical transfer function of the oil cooler system. The control performance and robustness were investigated by comparing indicial responses and Bode diagram analysis with respect to three kinds of PI gains obtained from different gain decision manners. Moreover, the robustness against to input disturbances, sinusoidal wave form and abrupt single pulse, was evaluated. The computer simulation results showed that the suggested optimum gain can establish desirable control performance and strong robustness with easy design process.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.15-22
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• 2005

In this paper, we propose a PID-PD controller and its tuning method to be modified form of PID controller that consist of the affine set of PID and PI-PD controller by analyzing relation between these controllers. The proposed tuning method controls the closed-loop system to locate between the step responses of system controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost functions. Its effectiveness is examined by the case studies and their analysis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.19-24
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• 2007

In this paper, we propose a tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller consists of the convex set of PID and PI-PD controller. PID-PD controller controls the closed-loop response to be located between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.135-142
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• 2008

This paper deals with the design of a robust PI controller for a vehicle suspension system. A method, which is related to computation of all stabilizing PI controllers, is applied to the vehicle suspension system in order to obtain optimum control between passenger comfort and driving performance. The PI controller parameters are calculated by plotting the stability boundary locus in the $(k_p,\;k_i)$-plane and illustrative results are presented. In reality, like all physical systems, the vehicle suspension system parameters contain uncertainty. Thus, the proposed method is also used to compute all the parameters of a PI controller that stabilize a vehicle suspension system with uncertain parameters.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.628-631
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• 2005

In this paper, we propose tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller that consist of the convex set of PID and PI-PD controller controls the closed-loop response to locate between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.

• Journal of Power Electronics
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• v.10 no.3
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• pp.306-312
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• 2010

In this paper, the design of an optimum single input Fuzzy controller for application in dc to ac converters is presented. Contrary to conventional Fuzzy controllers, the proposed controller has a smaller number of rules and tuning parameters but is capable of performing identically to a conventional controller. These benefits lead to a simpler controller design. The controller is designed as a PI controller for small-signal disturbances. However, for optimum large-signal performance, heuristic tuning is used. The tuning is less complicated and hence optimum large-signal performance is achievable. The system is simulated and a hardware prototype was developed for comparison purposes.

• 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.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.225-227
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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 artificial intelligent-PI(AIPI) 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.