• Title/Summary/Keyword: robust adaptive fuzzy control

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Robust Indirect Adaptive Fuzzy Controller for Balancing and Position Control of Inverted Pendulum System

  • Kim Yong-Tae;Kim Dong-Yon;Yoo Jae-Ha
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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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.

Robust adaptive fuzzy controller for an inverted pendulum

  • Seo, Sam-Jun;Kim, Dong-Sik
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1267-1271
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    • 2003
  • This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

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Robust Adaptive Fuzzy Backstepping Control for Trajectory Tracking of an Electrically Driven Nonholonomic Mobile Robot with Uncertainties (불확실성을 가지는 전기 구동 논홀로노믹 이동 로봇의 궤적 추종을 위한 강인 적응 퍼지 백스테핑 제어)

  • Shin, Jin-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.10
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    • pp.902-911
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    • 2012
  • This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

A Robust Indirect Adaptive Fuzzy State Feedback Regulator Based on Takagi-Sugeno Fuzzy Model

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.6
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    • pp.554-558
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

T-S Model Based Robust Indirect Adaptive Fuzzy Control

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.211-214
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

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T-S Fuzzy Model Based Robust Indirect Adaptive State Feedback Control of Flexible Joint Manipulators

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1471-1474
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

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Robust Adaptive Fuzzy Tracking Control Using a FBFN for a Mobile Robot with Actuator Dynamics (구동기 동역학을 가지는 이동 로봇에 대한 FBFN을 이용한 강인 적응 퍼지 추종 제어)

  • Shin, Jin-Ho;Kim, Won-Ho;Lee, Moon-Noh
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.4
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    • pp.319-328
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    • 2010
  • This paper proposes a robust adaptive fuzzy tracking control scheme for a nonholonomic mobile robot with external disturbances as well as parameter uncertainties in the robot kinematics, the robot dynamics, and the actuator dynamics. In modeling a mobile robot, the actuator dynamics is integrated with the robot kinematics and dynamics so that the actuator input voltages are the control inputs. The presented controller is designed based on a FBFN (Fuzzy Basis Function Network) to approximate an unknown nonlinear dynamic function with the uncertainties, and a robust adaptive input to overcome the uncertainties. When the controller is designed, the different parameters for two actuator models in the actuator dynamics are taken into account. The proposed control scheme does not require the kinematic and dynamic parameters of the robot and actuators accurately. It can also alleviate the input chattering and overcome the unknown friction force. The stability of the closed-loop control system including the kinematic control system is guaranteed by using the Lyapunov stability theory and the presented adaptive laws. The validity and robustness of the proposed control scheme are shown through a computer simulation.

Robust Adaptive Fuzzy Controller Using a Sliding Control Input (슬라이딩 제어 입력을 이용한 강인 적응 퍼지 제어기)

  • 이선우;박윤서
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.03a
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    • pp.35-38
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    • 1998
  • Abstracts In this paper, we propose a robust adaptive fuzzy control scheme using a sliding control input for tracking of a class of MISO nonlinear systems with unknown bounded external disturbances. In the proposed scheme, the nonlinearity is estimated adaptively via a fuzzy inference based on a fuzzy model. A sliding control input is introduced such that boundedness of all signals in the system is guaranteed even though the existence of a fuzzy approximation error and external disturbances. The controller parameters are updated by using a proposed adaptation law, which is similar 1-modification method. Computer simulation shows the effectiveness of the proposed control scheme.

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Control of Inverted Pendulum using Robust Adaptive Fuzzy Controller (강인한 적응 퍼지 제어기를 이용한 도립 진자 제어)

  • Seo, Sam-Jun;Kim, Dong-Sik
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2441-2443
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    • 2003
  • This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

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A Study on an Adaptive Robust Fuzzy Controller with GAs for Path Tracking of a Wheeled Mobile Robot

  • Nguyen, Hoang-Giap;Kim, Won-Ho;Shin, Jin-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.1
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    • pp.12-18
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    • 2010
  • This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. Genetic algorithms are employed to optimize the fuzzy rules of FBFN. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations.