• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.63-71
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• 2000

This paper deals with a systematic approach to GA-PI controller design for static VAR compensator(SVC) using genetic algorithm(GA) to improve system stability. Genetic algorithms(GAs) are search algorithms based on the mechanics of natural selection and natural genetics. To verify the validity of the proposed method, investigated damping ratio of the eigenvalues of the electro-mechanical modes system with and without SVC. Also, we considered dynamic response of terminal speed deviation and terminal voltage deviation by applying a power fluctuation at heavy load, normal load and light to verify the robustness of the proposed. Thus, we proved usefulness of GA-PI controller design to improve the stability of single machine-bus with SVC system.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.211-214
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• 2000

The conventional PI controller has been widely used in industrial application due to the simple control algorithm. But it is very difficult to find the optimal PI control gain. Therefore in this paper to obtain optimal performance fuzzy proportional-plus-integral controller for the vector control system of an induction machine is presented. The simulation model is created in MATLAB/SIMULINK. The simulation results demonstrate the good performance of this system.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.413-417
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• 2004

This paper proposes a fuzzy proportional-Integral (PI) controller for the precise tracking control of optical disk systems based on the genetic algorithm (GA). The fuzzy PI control rules are optimized by the GA to yield an optimal fuzzy PI controller. We validate the feasibility of the proposed method through a numerical simulation.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.11
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• pp.1068-1076
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• 2004

Technology on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the Environment Chamber experiment and a theoretical analysis was also conducted using TRNSYS program.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1168-1172
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• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.10
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• pp.1529-1535
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• 2012

This paper presents the application algorithm for speed control of Switched Reluctance Motor. The conventional PI controller has been widely used in industrial applications. But it is very difficult to find the optimal PI control gain. Fuzzy control does not need any model of plant. It is based on plant operator experience and heuristics. The proposed fuzzy logic modifier increases the control performance of conventional PI controller. Simulation and experimental results show that the proposed fuzzy control method was superior to the conventional PI controller in the respect of system performance. The experiments are performed to verify the capability of proposed control method on 6/4 salient type SRM.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.411-419
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• 1998

In this paper the steady-state genetic algorithm is applied for the optimal design of fuzzy PID controllers. Basically the structure of the discussed fuzzy PID controller is extended from the conventional fuzzy PI and PD controllers where only a two-dimensional rule base of the fuzzy PID controller are designed simultaneously. Simulations results shows the superior performance of this optimal designed fuzzy PID controllers to the optimal designed conventional fuzzy PI and PD controllers.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.186-189
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• 2003

This paper presents an optimal tuning method of the decentralized PI controller of two-input, two-output(TITO) second order system to be formulated as LQR. The tuning method of proposed decentralized PI controller is developed by establishing the relationships between the closed-loop state equation including decentralized PI control factors and the closed-loop state equation of LQR, which can be guaranteed the performance and stability-robustness by selecting the weighting factors Q and R of the cost function in order to satisfy design specifications in frequency domain.