• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.728-731
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• 1997

This paper proposes the systematic auto-tuning method for fuzzy controller using genetic algorithm(GA). In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge and relies to a great extent on heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored. Proposed genetic algorithm searches the optimal rule structure, parameters of membership functions and scaling factors simultaneously and automatically by a new genetic coding format. Inverted pendrum system is provided to show the advantages of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.36-42
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• 1996

In this paper, we proposed a PID controller, which could control unknown plants using Artificial Neural Network(ANN) for auto-tuning of the PID parameters. In the proposed algorithm, the parameters of the controller were adjusted to reduce the error of the controlled plant. In this process, the sensitivity between input and output of the unknown plant was needed. So, in order to obtain this sensitivity, the ANN's learnig ability was used. Computer simualtions were performed for the regulation problems, and the results were compared with those of Ziegler-Nichols PID controller. As a result, it was shown that the proposed algorithm outperformed Ziegler-Nichols controller in rise time, overshoot, undershoot, and setting time.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.941-954
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• 1991

The characteristics of a power plant changes as it operates for a long time and/or for different operating point. As a result, operators must retune gains of the controllers for better performance. In fact, skilled operators can retune the gains in reference to recorded data obtained by a test called dynamic test. The dynamic test, however, requires much time, and can be heavy burden for operators. In this paper, an expert knowledge-based auto-tuner is designed for drum-type boiler controllers of a fossil power plant using fuzzy logic. The performance of the proposed auto-tuner is shown via computer simulation and the simulation results show that the proposed auto-tuner is satisfactory for the desired performance.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2651-2654
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• 2000

In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a self tuning fuzzy PID controller whose input output scaling factors were tuned automatically. At first stage, the tuning parameters of fuzzy controller were determined by Ziegler-Nichols tuning method and then they were adjusted as the delay time and process environment were changed. Proposed controller was simple in its structrue and computational burden was small so that on line adaptation was easy to apply to. The result of computer simulation and practical experiment showed the proposed controller's excellent performance

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2584-2586
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• 2000

A drum level control is one of the most important control systems in thermal power plant. The control objective of drum level of boiler in thermal power plant is to maintain drum level at constant set-point regardless of disturbance such as main steam flow. The implemented drum level controller is the cascade PI controller. The important factor in drum level controller is the parameters of two PI controllers. The tuning of PI controller parameter is tedious and time-consuming job. In this paper, the relay feedback Ziegler - Nichols tuning method extended to auto-tune cascade PI drum level controller. Finally, the simulation result using boiler model in Power Plant shows the validity of auto-tuned cascade PI controller.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.695-698
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• 1995

The shape and width of fuzzy membership function has an effect on performance of fuzzy controller. In this paper, fuzzy controller is proposed to improve the control performance of fuzzy controller. It has two fuzzy inference engine. The one is typical fuzzy inference engine, the other is proposed to infer optimal width of membership function in fuzzy controller from plant constant (K,T,L). To show the effectiveness of this fuzzy controller with double fuzzy inference engine, it is applied to plant (dead time + 1st order delay) with various plant constant.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.217-224
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• 1998

During the operation of crane system in container yard, the objective is to transport the load to a goal position as quick as possible without rope oscillation. The container crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. Therefore, we developed an optimal controller which has to control the crane system with disturbances. In this paper, we present a design of optima 2-DOF PID controller for the control of gantry crane which has to control swing motion and trolley position. We used evolution strategy(ES) to tune the parameters of 2-DOF PID controller. It was compared with general PID controller. The computer simulations show that the proposed method has better performances than the other method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.3
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• pp.57-66
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• 2001

This paper resents a control approach for designing a fuzzy-PI controller for a synchronous generator excitation and SVC system A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the must fiexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage A Fuzzy-PI controller for SVC system was proposed in this paper. The PI gain parameters of the proposed Fuzzy-PI controller which is a special type of PI ones are self-tuned by fuzzy inference technique. It is natural that the fuzzy inference technique should be barred on humans intuitions and empirical knowledge. Nonetheless, the conventional ones were not so. Therefore, In this paper, the fuzzy inference technique of PI gains using MMGM(Min Max Gravity Method) which is very similar to humans inference procedures, was presented and allied to the SVC system. The system dynamic responses are examined after applying all small disturbance condition.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2299-2301
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• 2000

In this paper, the design of PID controller using Neural networks for the control of non-linear system is presented. First, non-linear system is identified using BPN(Backpropagation Network) algorithm. This identified model is connected to the PID controller and the parameters of PID controller are updated to the direction of reducing the difference between the identified model output and model reference output in arbitrary input signal. Therefore, identified model output tracks the model reference output in an acceptable error range and the parameters of controller are updated adaptively. The output of the system has a good performance in case of both noisy and noiseless model reference and we can control the system stable in off-line when the dynamics of the system is changed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.55-61
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• 2000

In this paper, we proposed a new PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kc, $\tau$I, $\tau$D by the Ziegler-Nichols formula using the ultimate gain and ultimate period from a relay tuning experiment. We get error and error change of plant output correspond to the initial value and new proportion gain(Kc) and integral time($\tau$I) from fuzzy tunner. This fuzzy tuning algorithm for PID controller considerably reduced overshoot and rise time compare to any other PID controller tuning algorithms. In real parametric uncertainty systems, the PID controller with Fuzzy auto-tuning give appreciable improvement in the performance. The significant properties of this algorithm is shown by simulation In this paper, we proposed a new PID algorithm by the fuzzy set theory to improve the performance of the PID controller.