• 한국정밀공학회지
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• 제12권4호
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• pp.111-118
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• 1995

This paper presents the modified fuzzy-compensated PID(FCPID) control, which involves adding the compensator to an existing PID controller, to improve the performances of the systems. Compared to a conventional PID control and a fuzzy logic control(FLC), the proposed control scheme has superior performance. Experimental results of an actual implementation of the modified PC-based FCPID controller on the DC servo-motor demonstrate considerable improve- ment of the performance of the existing FCPID control by monitoring the scaling factor. They show faster responses and smaller overshoots than the conventional FCPID control scheme for the various reference inputs and the robustness to the loads.

• 한국정보통신학회논문지
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• 제19권1호
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• pp.26-34
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• 2015

본 논문에서는 이동 로봇의 군집 제어를 위해 퍼지 보상된 PID 제어 시스템을 제안한다. 제어 시스템은 선도-추종기법에 기반한 기구학 제어기와 이동 로봇의 동역학적 영향을 고려한 동역학 제어기로 구성되어 있다. 이동 로봇의 대형 유지를 위해 동역학 제어기는 PID제어기로 구성되었다. 하지만 PID 제어기는 비선형 또는 환경 변화에 취약점을 가진다. 이러한 문제를 보완하기 위해 퍼지 보상기를 추가하였다. 마지막으로 개선된 성능을 보이기 위해 컴퓨터 시뮬레이션을 통해 제안된 제어기를 평가하였다.

• 제어로봇시스템학회논문지
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• 제1권1호
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• pp.50-57
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• 1995

In this paper, the design and the implementation of the controller for an articulate robot, which is developed in our Automatic Control Laboratory, are mainly discussed. The controller reduces software computational load via distributed processing method using multiple CPU's, and simplifies structures by the time-division control with TMS320C31 DSP chip. The method of control is based on the fuzzy-compensated PID control with scale factor, which compensates for the influence of load variation resulting from the various postures of the robot with conventional PID scheme. The application of the proposed controller to the robot system with DC servo-motors shows some excellent control capabilities. Also, the response characteristics of system for the various trajectory commands verify the superiority of the controller.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.671-676
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• 2007

In this paper, a novel neuro-fuzzy controller is presented. The generic fuzzy controller is compensated by a neural network controller so that an overall control structure forms a neuro-fuzzy controller. The proposed neuro-fuzzy controller solves the difficulty of selecting optimal fuzzy rules by providing the similar effect of modifying fuzzy rules simply by changing crisp input values. The performance of the proposed controller is tested by controlling humanoid robot arms. The humanoid robot arm is analyzed and implemented. Experimental studies have shown that the performance of the proposed controller is better than that of a PID controller and of a generic fuzzy PD controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.173-174
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• 2007

In this paper, a new speed sensorless control based on an instantaneous reactive power and a fuzzy PI compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional fixed gain PI and PID controllers are very sensitive to step change of command speed, parameter variations and load disturbance. Also, to the estimated speeds are compensated by using an instantaneous reactive power in synchronously rotating reference frame. In a fuzzy compensator, the system control parameters are adjusted by a fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.