• Title/Summary/Keyword: dynamic fuzzy control

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STABILITY OF FUZZY DYNAMIC CONTROL SYSTEM: The Cell-State Transition Method

  • Kang, Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1078-1081
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    • 1993
  • The Objective of this paper is to provide fuzzy control designers with a design tool for stable fuzzy logic controllers. Given multiple sets of data disturbed by vagueness uncertainty, we generate the implicative rules that guarantee stability and robustness of closed-loop fuzzy dynamic systems. We propose the cell-state transition method which utilizes Hsu's cell-to-cell mapping concept [1]. As a result, a generic and implementable design methodology for obtaining a fuzzy feedback gain K, a fuzzy hypercube [2], is provided and illustrated with simple examples.

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Hybrid control of a tricycle wheeled AGV for path following using advanced fuzzy-PID

  • Bui, Thanh-Luan;Doan, Phuc-Thinh;Van, Duong-Tu;Kim, Hak-Kyeong;Kim, Sang-Bong
    • Journal of Advanced Marine Engineering and Technology
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    • v.38 no.10
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    • pp.1287-1296
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    • 2014
  • This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

Design of Robust Adaptive Fuzzy Controller for Uncertain Nonlinear System Using Estimation of Bounding Constans and Dynamic Fuzzy Rule Insertion (유계상수 추정과 동적인 퍼지 규칙 삽입을 이용한 비선형 계통에 대한 강인한 적응 퍼지 제어기 설계)

  • Park, Jang-Hyun;Park, Gwi-Tae
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.1
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    • pp.14-21
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    • 2001
  • This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. In indirect adaptive fuzzy control, based on the proved approximation capability of fuzzy systems, they are used to capture the unknown nonlinearities of the plant. Until now, most of the papers in the field of controller design for nonlinear system considers the affine system using fuzzy systems which have fixed grid-rule structure. We proposes a dynamic fuzzy rule insertion scheme where fuzzy rule-base grows as time goes on. With this method, the dynamic order of the controller reduces dramatically and an appropriate number of fuzzy rules are found on-line. 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.

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Direct Torque Control of Squirrel Cage Typed Induction Motor Using Fuzzy Controller (퍼지제어기를 이용한 농형 유도 전동기의 직접 토크제어)

  • Han, Sang-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.1
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    • pp.122-129
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    • 2008
  • The direct torque control method of an inverter fed squirrel cage typed induction motor using fuzzy logic controller has been proposed. This method is suitable for the traction which requires a fast torque response during the star-up and step change. The fuzzy control algorithm based upon the control principles of conventional DSC(Direct Self Controller) is developed. The fuzzy algorithm is tarried out by defuzzification strategy of the fuzzy output extracted from the possibility distribution of an inferred fuzzy control rule. The flux and torque of an induction motor are estimated by the dynamic model of the rotor flux field-oriented scheme which has decoupling characteristics and excellent dynamic response over a wide speed range. The proposed controller shows a good dynamic response. Moreover, since the fuzzy controller possesses highly adaptive capability, the performance of fuzzy controller is quite robust and insensitive to the motor parameters and change of operation conditions.

Position/Force Control of Robotic Manipulator with Fuzzy Compensation (퍼지 보상을 이용한 로봇 매니퓰레이터의 위치/힘제어)

  • 심귀보
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.3
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    • pp.36-51
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    • 1995
  • An approach to robot hybrid position/force control, which allows force manipulations to be realized without overshoot and overdamping while in the presence of unknown environment, is given in this paper. The manin idea is to used dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify the unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resovled acceleration control method, dynamic compensation and PD control based on known robot dynamics, kinematics and estimated environment stiffness is introduced. To avoid overshoot the whole control system is constructed with overdamping. In the second stage, the unknown environment stiffness is identified by using fuzzy reasoning, where the fuzzy compensation rules are obtained priori as the expression of the relationship betweenenvironment stiffness and system. Based on the simulation result, comparison between cases with or without fuzzy identifications are given, which illustrate the improvement achieced.

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Force control of robot manipulator using fuzzy concept

  • Sim, Kwee-Bo;Xu, Jian-Xin;Hashimoto, Hideki;Harashima, Fumio
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.907-912
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    • 1990
  • An approach to robot force control, which allows force manipulations to be realized without overshot and overdamping while in the presence of unknown environment, is given in this paper. The main idea is to use dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resolved acceleration control method, dynamic compensation and PID control based on known robot dynamics, kinematics and estimated environment compliance is introduced. To avoid overshoot the whole control system is constructed overdamped. In the second stage, the unknown environment stiffness is estimated by using fuzzy reasoning, where the fuzzy estimation rules are obtained priori as the expression of the relationship between environment stiffness and system response. Based on simulation result, comparisons between cases with or without fuzzy identifications are given, which illustrate the improvement achieved.

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Control of Humanoid Robots Using Time-Delay-Estimation and Fuzzy Logic Systems

  • Ahn, Doo Sung
    • Journal of Drive and Control
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    • v.17 no.1
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    • pp.44-50
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    • 2020
  • For the requirement of accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Because of the complexity of humanoid robot dynamics, the TDC (time-delay control) is practical because it does not require a dynamic model. However, there occurs a considerable error due to discontinuous non-linearities. To solve this problem, the TDC-FLC (fuzzy logic compensator) is applied to humanoid robots. The applied controller contains three factors: a TDE (time-delay estimation) factor, a desired error dynamic factor, and FLC to suppress the TDE error. The TDC-FLC is easy to execute because it does not require complicated humanoid dynamic calculations and the heuristic fuzzy control rules are intuitive. TDC-FLC is implemented on the whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the TDC-FLC for humanoid robots.

Dynamic Responses and Fuzzy Control of a Simply Supported Beam Subjected to a Moving Mass

  • Kong, Yong-Sik;Ryu, Bong-Jo;Shin, Kwang-Bok;Lee, Gyu-Seop;Lee, Hong-Gi
    • Journal of Mechanical Science and Technology
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    • v.20 no.9
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    • pp.1371-1381
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    • 2006
  • This paper deals with the active vibration control of a simply-supported beam traversed by a moving mass using fuzzy control. Governing equations for dynamic responses of a beam under a moving mass are derived by Galerkin's mode summation method, and the effect of forces (gravity force, Coliolis force, inertia force caused by the slope of the beam, transverse inertia force of the beam) due to the moving mass on the dynamic response of a beam is discussed. For the active control of dynamic deflection and vibration of a beam under the moving mass, the controller based on fuzzy logic is used and the experiments are conducted by VCM (voice coil motor) actuator to suppress the vibration of a beam. Through the numerical and experimental studies, the following conclusions were obtained. With increasing mass ratio y at a fixed velocity of the moving mass under the critical velocity, the position of moving mass at the maximum dynamic deflection moves to the right end of the beam. With increasing velocity of the moving mass at a fixed mass ratio ${\gamma}$, the position of moving mass at the maximum dynamic deflection moves to the right end of the beam too. The numerical predictions of dynamic deflection of the beam have a good agreement with the experimental results. With the fuzzy control, more than 50% reductions of dynamic deflection and residual vibration of the tested beam under the moving mass are obtained.

Dynamic Control of Track Vehicle Using Fuzzy-Neural Control Method (퍼지-뉴럴 제어기법에 의한 궤도차량의 동적 제어)

  • 한성현;서운학;조길수;윤강섭
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.04a
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    • pp.133-139
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    • 1997
  • This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is propored a learning controller consisting of two neural network-fuzzy based on independent resoning and a connection net with fixed weights to simply the neural network-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle

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An alternative portable dynamic positioning system on a barge in short-crested waves using the fuzzy control

  • Fang, Ming-Chung;Lee, Zi-Yi
    • Ocean Systems Engineering
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    • v.5 no.3
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    • pp.199-220
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    • 2015
  • The paper described the nonlinear dynamic motion behavior of a barge equipped with the portable outboard Dynamic Positioning(DP) control system in short-crested waves. The DP system based on the fuzzy theory is applied to control the thrusters to optimally adjust the ship position and heading in waves. In addition to the short-crested waves, the current, wind and nonlinear drifting force are also included in the calculations. The time domain simulations for the six degrees of freedom motions of the barge with the DP system are solved by the $4^{th}$ order Runge-Kutta method. The results show that the position and heading deviations are limited within acceptable ranges based on the present control method. When the dynamic positioning missions are needed, the technique of the alternative portable DP system developed here can serve as a practical tool to assist those ships without equipping with the DP facility.