• Title/Summary/Keyword: adaptive fuzzy sliding mode control

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Fuzzy Rule Reduction Algorithms and the Reconstruction of Fuzzy System using Decomposition of Nonlinear Functions (비선형 함수의 분해를 이용한 퍼지시스템의 재구성과 퍼지규칙수 줄임 알고리즘)

  • 유병국
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.2
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    • pp.95-102
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    • 2001
  • Fuzzy system is capable of uniformly approximating any nonlinear function over compact input space. The applications of fuzzy system, however, have been primarily limited by the need for large number of fuzzy rules, in particular, for the high-order nonlinear system. In this paper, we propose the reconstruction methods of fuzzy systems, parallel type and cascade, based on the decomposition of some classes of high-order nonlinear functions. Using the both types appropriately, we can reduce the number of fuzzy rules geometrically. It can be applied to the fuzzy system that has an online adaptive structure. Two examples of adaptive fuzzy sliding mode control are shown in the computer simulations to verify the validity of the proposed algorithm.

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Efficiency Optimization with Sliding Mode Observer for Induction Motor (슬라이딩 모드 관측기를 이용한 유도전동기의 효율 최적화)

  • Lee, Sun-Young;Park, Ki-Kwang;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 2009.04a
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    • pp.74-76
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    • 2009
  • In this paper, search method and sliding mode observer are developed for efficiency optimization of induction motor. The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. The search controller is based on the "Rosenbrock" method and finds the flux level at the minimum input power of induction motor. Once this optimal flux level has been determined, this information is utilized to update the rule base of a fuzzy controller A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is also used to compensate for mechanical uncertainties in the speed control of induction motor. Simulation results are presented to validate the proposed controller.

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Ride Comfort Evaluation of Seat Suspension of Commercial Vehicle with MR Damper (MR 댐퍼를 장착한 상용차 시트 서스팬션의 승차감 평가)

  • Shin, Do-Kyun;Do, Xuan Phu;Choi, Seung-Bok
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2014.10a
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    • pp.32-33
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    • 2014
  • This paper presents control performances of a seat suspension system equipped with magnetorheological (MR) dampers using a new adaptive fuzzy sliding mode controller (FSMC). Adaptive fuzzy controller is formulated by considering the acceleration of the seat. It has been demonstrated that the proposed seat suspension system realized by the adaptive fuzzy sliding mode controller can provide effective performances such as reduced vibration.

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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.

Adaptive fuzzy sliding mode control (적응 퍼지 슬라이딩 모드 제어)

  • Yoo, Byung-Kook;Jeoung, Sa-Cheul;Ham, Woon-Chul
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.4
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    • pp.287-296
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    • 1996
  • 본 논문에서는 퍼지추정기와 슬라이딩 모드제어이론이 고려되었다. 비선형시스템에 대한 슬라이딩 모드 제어기 설계 시에 그 시스템의 비선형함수를 추정하기 위하여 퍼지논리시스템이 사용되는 두가지의 적응처지슬라이딩 모드제어방식을 제안한다. 첫번째 방식에서는 비선형시스템, x/sup (n)/=f(x under bar, t) + b(x under bar, t)u 의 알지 못하는 함수 f를 추정하기 위하여 하나의 퍼지논리시스템이 사용되어진다. 두번째 방식에서는 비선형시스템의 f와 b에 대한 추정기로서의 두개의 퍼지논리시스템이 각각 사용되어진다. 각각의 방식에 대하여 제어시스템의 안정도를 보장하도록 하는 적응법칙을 설계하며 퍼지추정기와 비선형함수와의 추정오차를 줄이기 위해 각각에 대한 강인한 제어법칙을 제안한다. 제안된 네 가지의 제어법칙에 대한 안정성을 증명하고 컴퓨터시뮬레이션에서 역진자시스템에 적용하여 그에 대한 타당성과 각각의 비교를 보인다.

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Adaptive Fuzzy Sliding Mode Control of Brushless DC Motor (브러시리스 DC 모터의 적응퍼지 슬라이딩 모드 제어)

  • Lee, Jong-Ho;Kim, Sung-Tae;Kim, Young-Tas
    • Proceedings of the KIEE Conference
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    • 2000.11d
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    • pp.647-649
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    • 2000
  • Brushless DC motors are widely used in many industrial fields as an actuator of robot and driving power motors of electrical vehicle. In this paper adaptive fuzzy sliding mode scheme is developed for velocity control of brushless DC motor. The proposed scheme does not require an accurate dynamic model. yet it guarantees asymptotic trajectory tracking despite torque variations. Numerical simulation and DSP-based experimental works for velocity control of brushless DC motor are carried out.

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Multiple Faults Detection and Isolation via Decentralized Sliding Mode Observer for Reconfigurable Manipulator

  • Zhao, Bo;Li, Chenghao;Ma, Tianhao;Li, Yuanchun
    • Journal of Electrical Engineering and Technology
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    • v.10 no.6
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    • pp.2393-2405
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    • 2015
  • This paper considers a decentralized multiple faults detection and isolation (FDI) scheme for reconfigurable manipulators. Inspired by their modularization property, a global sliding mode (GSM) based stable adaptive fuzzy decentralized controller is investigated for the system in fault free, while for the system suffering from multiple faults (actuator fault and sensor fault), the decentralized sliding mode observer (DSMO) is employed to detect their occurrence. Hereafter, the time and location of faults can be determined by a fault isolation scheme via a bank of DSMOs. Finally, the effectiveness of the proposed schemes in controlling, detecting and isolating faults is illustrated by the simulations of two 3-DOF reconfigurable manipulators with different configurations successfully.

Robust Adaptive Backstepping Control of Induction Motors Using Nonlinear Disturbance Observer (비선형 외란 관측기를 이용한 유도전동기의 강인 적응 백스테핑 제어)

  • Lee, Eun-Wook
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.57 no.2
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    • pp.127-134
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    • 2008
  • In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

Robust Adaptive Control for Efficiency Optimization of Induction Motors (유도전동기의 효율 최적화를 위한 강인 적응제어)

  • Hwang, Young-Ho;Park, Ki-Kwang;Kim, Hong-Pil;Han, Hong-Seok;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.1505-1506
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    • 2008
  • In this paper, a robust adaptive backstepping control is developed for efficiency optimization of induction motors with uncertainties. The proposed control scheme consists of efficiency flux control(EFC) using a sliding mode adaptive flux observer and robust speed control(RSC) using a function approximation for mechanical uncertainties. In EFC, it is important to find the flux reference to minimize power losses of induction motors. Therefore, we proposed the optimal flux reference using the electrical power loss function. The sliding mode flux observer is designed to estimate rotor fluxes and variation of inverse rotor time constant. In RSC, the unknown function approximation technique employs nonlinear disturbance observer(NDO) using fuzzy neural networks(FNNs). The proposed controller guarantees both speed tracking and flux tracking. Simulation results are presented to illustrate the effectiveness of the approaches proposed.

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Nonlinear Friction Control Using the Robust Friction State Observer and Recurrent Fuzzy Neural Network Estimator (강인한 마찰 상태 관측기와 순환형 퍼지신경망 관측기를 이용한 비선형 마찰제어)

  • Han, Seong-Ik
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.18 no.1
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    • pp.90-102
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    • 2009
  • In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.