• Title/Summary/Keyword: Fuzzy-compensated PID controller

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A Study on Design of the Modified Fuzzy-Compensated PID Controller (개선된 퍼지보상 PID제어기 설계에 관한 연구)

  • Lee, H.J.;Kim, J.G.
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.4
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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.

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A Study on the Design of Compensated Fuzzy Controller (보상형 퍼지 제어기 설계에 관한 연구)

  • 추연규;탁한호
    • Journal of the Korean Institute of Navigation
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    • v.24 no.3
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    • pp.141-145
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    • 2000
  • In servo-system which need fast response and accuracy, PID controller has a good steady-state performance, but has a poor transient response performance causing a load be changed. Compared to these features, FLC(Fuzzy Logic Controller) has a good transient response performance for changed load, but has a little Poor steady-state performance. In this paper, Compensated Fuzay Controller which consists of PID controller and FLC is proposed to modify these disadvantages and is examined through simulation to evaluate its functions.

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A Formation Control Scheme for Mobile Robots Using a Fuzzy Compensated PID Controller (이동 로봇 군집 제어를 위한 퍼지 보상 PID제어기)

  • Bae, Ki-Hyun;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.1
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    • pp.26-34
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    • 2015
  • In this paper, a fuzzy compensated PID control system is proposed for formation control of mobile robots. The control system consists of a kinematic controller based on the leader-follower approach and a dynamic controller to handle dynamics effects of mobile robots. To maintain the desired formation of mobile robots, the dynamic controller is equipped with a PID controller; however, the PID controller has poor performance in nonlinear and changing environments. In order to improve these problem, we applied the additional fuzzy compensator. Finally, the proposed control system has been evaluated through computer simulation to demonstrate the improved results.

Development of robot control system using DSP (DSP를 이용한 로보트 제어시스템 개발)

  • Lee, Bo-Hee;Kim, Jin-Geol
    • Journal of Institute of Control, Robotics and Systems
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    • v.1 no.1
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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.

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Experimental Studies of a Fuzzy Controller Compensated by Neural Network for Humanoid Robot Arms (다관절 휴머노이드 상체 로봇의 제어를 위한 신경망 보상 퍼지 제어기 구현 및 실험)

  • Song, Deok-Hui;Noh, Jin-Seok;Jung, Seul
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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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.