• 전자공학회논문지B
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• 제30B권7호
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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.

• 수산해양기술연구
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• 제26권1호
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• pp.76-80
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• 1990

비선형의 특성을 갖고 있는 DC 서보 모터의 속도 제어에 퍼지 제어기의 사용을 제안하였다. 퍼지 제어기는 퍼지 모델로부터 설계되며, 그 퍼지 모델은 시스템의 입출력 데이터로 인식되고 비선형 시스템의 표현에 뛰어난 능력을 갖고 있다. 따라서 퍼지 모델로부터 설계되는 퍼지 제어기는 시스템의 비선형 특성이 잘 반영되어지며 그러한 점은 서보 모터의 속도 제어에 응용한 결과 잘 알 수 있었다. 즉 퍼지 제어기에 비해 고속 제어가 가능해졌으며 정상 리플(ripple)이 감소하였다. 또한 이 퍼지 제어기에서 사용되는 퍼지 집합의 멤버쉽 함수는 간단한 선형 구분 함수이므로 퍼지 제어기도 간략한 형태로 표현되었다

• 전자공학회논문지B
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• 제30B권5호
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• pp.109-119
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• 1993

To improve limitations of fuzzy PI controllers especially when applied to systems of order higher than one, we propose a fuzzy PI controller that takes out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the calculation of incremental control input as in the case of conventional fuzzy PI controllers. The structure of the proposed controller was motivated by the characteristics of fuzzy PI controller that it generally gives inevitable overshoot when one tries to reduce rise time of the response especially when a system of order higher than one is under consideration. Since the undesirable characteristics of the fuzzy PI controller is caused by integrator of the controller, even though the integrator is introduced to overcome steady state error of response, we propose a controller that fuzzily clears out integrated quantities according to situation to give reduced rise time as well as small overshoots. To show the usefulness of the proposed controller, it is applied in simulations to such systems as are difficult to stabilize or difficult to get satisfactory responses by conventional fuzzy PI controllers.

• Journal of Biosystems Engineering
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• 제20권1호
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• pp.87-94
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• 1995

When farmer loads and unloads farm products with a trailer, linked to a tractor, the tractor-trailer is backed up to the loading duck. However, travelling backward is not easy and takes a time for even skilled operators. Therefore, unmanned backing up is necessary to save the effort. A backward controller of tractor-trailer was simulated using fuzzy logic and genetic algorithms. Operators drive the tractor-trailer back and forth several times for backing up to the loading duck. As the operators did it, a backward controller was designed using fuzzy logic. And genetic algorithms was applied to improve the performance of the backward controller. With the strings coded with the fuzzy membership functions, genetic operations were carried out. After 30 generations, the best fitted fuzzy membership functions were found. Those membership functions were used in the fuzzy backward controller. The fuzzy controller combined with genetic algorithms showed the better results than the fuzzy controller did alone.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.179.5-179
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• 2001

Generally, while PD-type fuzzy controller has good performance in transient period, it has uniform steady state error of response. To improve limitations of PD-type fuzzy controller, we propose a new fuzzy controller to improve the performance of transient response and to eliminate the steady state error of response. In this paper, PD-type fuzzy controller is used a simplified indirect inference method(SIIM). When the SIIM is applied, the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. The outputs of this controller are the output calculated by PD-type fuzzy controller and the accumulated error scaling factor. Here, the accumulated error scaling factor is adjusted by fuzzy rule according to the system state variables. To show the usefulness of the proposed controller, it is applied to 0-type 2nd-order linear system.

• KIEE International Transaction on Systems and Control
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• 제12D권1호
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• pp.17-26
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• 2002

In this paper, a new design methodology of the fuzzy controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors. The design procedure is based on evolutionary computing (more specifically, a genetic algorithm) and estimation algorithm to adjust and estimate scaling factors respectively. The tuning of the soiling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as HCM (Hard C-Means) and Neuro-Fuzzy model[7]. The validity and effectiveness of the proposed estimation algorithm for the fuzzy controller are demonstrated by the inverted pendulum system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1496-1499
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• 2005

In this paper, we applied step motor drive using a fuzzy logic control based on PID controller. A designed this controller's purpose is improved robust and autonomous characteristic in which the variation of external load affects plant parameter. Therefore, in this paper, using a fuzzy logic control based on PID controller of two fuzzy-PI and fuzzy-D is obtained decremental overshoot and a special response quality.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1207-1210
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• 1993

There is an opinion of regarding a simple fuzzy logic controller as a kind of Variable Structure Controller in recent years. The opinion may provide an analytical basis which describes the robustness to uncertainty and the stability of a fuzzy logic controller. So in this paper, a fuzzy logic controller based on the Variable Structure System with is designed for a robot manipulator which is a class of complex, nonlinear system with uncertainty. Fuzzy control rules, membership shape of the I/O variables of the fuzzy logic controller are designed for guaranteeing the stability of an overall control system. From a computer simulation of dynamic control of a two link robot manipulator, the design procedure of the fuzzy logic controller is validated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.310-313
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor (IPMSM) drive New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzy described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzy clear out integrated quantities according to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for IPMSM drive system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.155-160
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• 2006

In the paper a robust indirect adaptive fuzzy controller is proposed for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the proposed fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing and a supervisory fuzzy controller which emulates heuristic control strategy and arbitrate two control objectives. It is proved that the signals in the overall system are bounded. Simulation results are given to verify the proposed adaptive fuzzy control method.