• Title/Summary/Keyword: fuzzy sliding

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Control and Operation of Hybrid Microsource System Using Advanced Fuzzy- Robust Controller

  • Hong, Won-Pyo;Ko, Hee-Sang
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.7
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    • pp.29-40
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    • 2009
  • This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

ACTIVE FAULT-TOLERANT CONTROL OF INDUCTION MOTOR DRIVES IN EV AND HEV AGAINST SENSOR FAILURES USING A FUZZY DECISION SYSTEM

  • Benbouzid, M.E.H.;Diallo, D.;Zeraoulia, M.;Zidani, F.
    • International Journal of Automotive Technology
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    • v.7 no.6
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    • pp.729-739
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    • 2006
  • This paper describes an active fault-tolerant control system for an induction motor drive that propels an Electrical Vehicle(EV) or a Hybrid one(HEV). The proposed system adaptively reorganizes itself in the event of sensor loss or sensor recovery to sustain the best control performance given the complement of remaining sensors. Moreover, the developed system takes into account the controller transition smoothness in terms of speed and torque transients. In this paper which is the sequel of (Diallo et al., 2004), we propose to introduce more advanced and intelligent control techniques to improve the global performance of the fault-tolerant drive for automotive applications(e.g. EVs or HEVs). In fact, two control techniques are chosen to illustrate the consistency of the proposed approach: sliding mode for encoder-based control; and fuzzy logics for sensorless control. Moreover, the system control reorganization is now managed by a fuzzy decision system to improve the transitions smoothness. Simulations tests, in terms of speed and torque responses, have been carried out on a 4-kW induction motor drive to evaluate the consistency and the performance of the proposed fault-tolerant control approach.

Adaptive Fuzzy Sliding Mode Control for Nonlinear Systems without Parameter Projection Method (파라미터 투영 기법이 필요 없는 비선형 시스템의 적응 퍼지 슬라이딩 모드 제어)

  • Seo, Sam-Jun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.4
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    • pp.499-505
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    • 2011
  • In this paper, we proposed an adaptive fuzzy sliding mode control for nonlinear systems without parameter projection method. By modifying the controller structure, the parameters of the estimated input gain function are guaranteed not being identically zero and it is shown that the control scheme will not cause any implementation problem even if the estimated value of input gain function is zero at any moment during on-line operations. Except for the input gain function which an approximate estimate for its lower bound is needed, the proposed control scheme does not assume a priori the exact values of the bounding parameters. Based on Lyapunov synthesis methods, the overall control system guarantees that the tracking error asymptotically converges to zero and that all signals involved in controller are uniformly bounded. This can be illustrated by the simulation results for an inverted pendulum system.

Design of Sliding Mode Controller with Auto-tuning Method

  • He, Wei;Zhai, Yujia
    • Journal of the Korea Convergence Society
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    • v.4 no.2
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    • pp.43-50
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    • 2013
  • Sliding mode control(SMC) are carried out in this literature. And to make the controllers perform better, fuzzy logic was chosen,it makes PID controller auto-tuning parameters and reduced the chattering problem of sliding mode control. Since SMC take error and derivative of error as inputs, after comparison some results are obtained.PID controller response faster yet sliding mode control is much steadier. However certain problems cannot be ignored that the chattering phenomenal cannot be reduced entirely and this motion may hurt the machine; this project only considered a simple system, there is no guarantee PID can work as well as in this case for a much more complex system. MATLAB simulink was the main approach to obtain the performance of the two controllers: to observe the control output of the two controllers, electric circuit and special controllers are designed and tested in MATLAB.

A Quantitative Analysis of the Nonlinearity of Fuzzy Logic Controller (퍼지논리 제어기의 비선형성의 정량적 해석)

  • Lee, Chul-Heui;Seo, Seon-Hak
    • Journal of Industrial Technology
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    • v.16
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    • pp.231-237
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    • 1996
  • In this paper, the nonlinear I/O characteristic of fuzzy logic controller is analyzed by using cell concept. Sources of the nonlinearity in a fuzzy logic controller include the fuzzification, the fuzzy reasoning and the defuzzification. A closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity is analyzed with respect to the conventional PID control and the sliding mode control.

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Fuzzy Variable Structure Control System for Fuel Injected Automotive Engines (연료분사식 자동차엔진의 퍼지가변구조 제어시스템)

  • Nam, Sae-Kyu;Yoo, Wan-Suk
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.7 s.94
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    • pp.1813-1822
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    • 1993
  • An algorithm of fuzzy variable structrue control is proposed to design a closed loop fuel-injection system for the emission control of automotive gasoline engines. Fuzzy control is combined with sliding control at the switching boundary layer to improve the chattering of the stoichiometric air to fuel ratio. Multi-staged fuzzy rules are introduced to improve the adaptiveness of control system for the various operating conditions of engines, and a simplified technique of fuzzy inference is also adopted to improve the computational efficiency based on nonfuzzy micro-processors. The proposed method provides an effective way of engine controller design due to its hybrid structure satisfying the requirements of robustness and stability. The great potential of the fuzzy variable structure control is shown through a hardware-testing with an Intel 80C186 processor for controller and a typical engine-only model on an AD-100 computer.

The Fuzzy Model-Based-Controller for the Control of SISO Nonlinear System (SISO 비선형 시스템의 제어를 위한 퍼지 모델 기반 제어기)

  • Chang, Wook;Kwon, Ok-Kook;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.528-530
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    • 1998
  • This paper addresses analysis and design of a fuzzy model-based-controller for the control of uncertain SISO nonlinear systems. In the design procedure, we represent the nonlinear system by using a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller via parallel distributed compensation and sliding mode control. Unlike other parallel distributed controllers. this globally stable fuzzy controller is designed without finding a common positive definite matrix for a set of Lyapunov equations, and has good tracking performance. Furthermore, stability analysis is conducted not for the fuzzy model but for the real underlying nonlinear system. A simulation is included for the control of the Duffing forced-oscillation system, to show the effectiveness and feasibility of the proposed fuzzy control method.

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A novel story on rock slope reliability, by an initiative model that incorporated the harmony of damage, probability and fuzziness

  • Wang, Yajun
    • Geomechanics and Engineering
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    • v.12 no.2
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    • pp.269-294
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    • 2017
  • This study aimed to realize the creation of fuzzy stochastic damage to describe reliability more essentially with the analysis of harmony of damage conception, probability and fuzzy degree of membership in interval [0,1]. Two kinds of fuzzy behaviors of damage development were deduced. Fuzzy stochastic damage models were established based on the fuzzy memberships functional and equivalent normalization theory. Fuzzy stochastic damage finite element method was developed as the approach to reliability simulation. The three-dimensional fuzzy stochastic damage mechanical behaviors of Jianshan mine slope were analyzed and examined based on this approach. The comprehensive results, including the displacement, stress, damage and their stochastic characteristics, indicate consistently that the failure foci of Jianshan mine slope are the slope-cutting areas where, with the maximal failure probability 40%, the hazardous Domino effects will motivate the neighboring rock bodies' sliding activities.

Design of Fuzzy Model Based Controller for Uncertain Nonlinear Systems

  • Wook Chang;Joo, Young-Hoon;Park, Jin-Bae;Guanrong Chen
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.185-189
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    • 1998
  • This paper addresses analysis and design of a fuzzy model-based-controller for the control of uncertain SISO nonlinear systems. In the design procedure, we represent the nonlinear system by using a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller via parallel distributed compensation and sliding mode control. Unlike other parallel distributed controllers, this globally stable fuzzy controller is designed without finding a common positive definite matrix for a set of Lyapunov equations, and has good tracking performance. The stability analysis is conducted not for the fuzzy model but for the real underlying nonlinear system. Furthermore, the proposed method can be applied to partially known uncertain nonlinear systems. A numerical simulation is performed for the control of an inverted pendulum, to show the effectiveness and feasibility of the proposed fuzzy control method.

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