• Title/Summary/Keyword: Adaptive Law

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Direct Adaptive Control of Nonminimum Phase Systems Using Novel Estimation Algorithm (새로운 추정 알고리즘을 이용한 비최소 위상 시스템의 직접 적응 제어)

  • Lee, Seon-Woo;Kim, Jong-Hwan
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.377-380
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    • 1992
  • This paper proposes a novel direct adaptive pole placement control algorithm which can be applied to continuous time nonminimum phase systems. The algorithm is based on Lyapunov's direct method. By introducing an auxiliary signal, a minimal error model is constructed in state space. Using the error model an estimation law is obtained via Lyapunov's second stability theorem. The global stability of the overall system is established.

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Design of a Speed Controller for the Synchronous Motor in Electric Vehicle (전기자동차용 동기기의 속도제어기 설계)

  • Hyun, Keun-Ho
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.239-240
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    • 2007
  • In this paper, a robust adaptive backstepping controller will be proposed for the speed control of permanent magnet synchronous motors in using electrical vehicles. Stator resistance, damping coefficient, load torque are considered as uncertainties and noise generated at applying load torque to motor is also considered. It shows that the backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the Proposed controller.

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Nonlinear System Identification using an Adaptive Nonlinear Recursive State-Space Filter and its performance analysis (ANRSS 필터를 이용한 비선형 시스템의 인식 및 성능분석)

  • Kim, Hyun-Sang;Nam, Sang-Won
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.937-940
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    • 1995
  • The purpose of this paper is to present a nonlinear system identification method, where an adaptive nonlinear recursive state-spare(ANRSS) filter is employed as its filter structure, and a variable step (VS) algorithm is applied as its adaptation law. To demonstrate the validity of the proposed method, some simulation results are included.

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Robust Adaptive Controller for MIMO Nonsquare Nonlinear Systems Using Universal Function Approximators

  • Park, Jang-Hyun;Seo, Ho-Joon;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.40.4-40
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    • 2001
  • This paper addresses the problem of designing robust adaptive output tracking control for a class of MIMO nonlinear systems which have different number of inputs and outputs The stability of the whole closed-loop system is guaranteed in the sense of Lyapunov and uniformly Itimately boundedness of the tracking error vector as well as estimated parameters are shown. In addition, we show that the restrictive assumptions on input gain matrix which is presumed in the past works can be eliminated by using proposed control law.

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Robust Adaptive Fuzzy Observer Based Synchronization of Chaotic Systems

  • Hyun, Chang-Ho;Kim, Eun-Tai;Park, Mi-Gnon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.341-344
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    • 2007
  • This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

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Autonomous Intelligent Cruise Control Using the Adaptive Fuzzy Control (퍼지 적응제어를 이용한 차량간격 제어 알고리즘에 관한 연구)

  • 장광수;최재성
    • Transactions of the Korean Society of Automotive Engineers
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    • v.4 no.6
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    • pp.175-186
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    • 1996
  • In Advanced Vehicle Control System(AVCS), Autonomous Intelligent Cruise Control(AICC) is generally understood to be a system that can be achieved in the near future without the demanding infrastructure components and technoloties. AICC is an automatic vehicle following system with no human engagement in the longitudinal vehicle direction. This paper presents a fuzzy control algorithm to develop the AICC system. The control performance was studied information of vehicles using computer simulations. The most improtant aspects of the work reported here are the adoption of the fuzzy adaptive control law, and the use of filtering concept to reduce the slinky effects that may appear in a formation of vehicles equipped with AICC systems. The simulation results demonstrate the effectiveness of the fuzzy adaptive AICC system and its beneficial effects on traffic flow.

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Design of a Robust Adaptive Backstepping Controller for a Chaos System with Disturbances (외란을 포함한 카오스시스템의 강인 적응 백스테핑 제어기 설계)

  • Hyun, Keun-Ho;Ka, Chool-Hyun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.54 no.3
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    • pp.119-128
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    • 2005
  • In this paper, an robust adaptive backstepping controller is proposed for the chaos system with disturbances. This controller will be applicable to the chaos system of strict-feedback form and utilize the saturation function for decreasing the effect of disturbances derived from unmodelled dynamics and external noise. It shows that backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the proposed controller.

Sliding mode control with adaptive VSS observer

  • Chen, Yi-Feng;Tsutomu Mita
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1924-1929
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    • 1991
  • The conventional sliding mode control and variable structure control (VSC) of nonlinear uncertain system are well known for their robust property and simplity of control law. However, the use of them is only pardonable on the assumption that the upper-bound of parameter variation or nonlinearity is known and that the complete information about state is available. Though the former has been solved with adaptive robust control theory recently, the latter seems not to be solved. In this paper, we try to solve this problem using the technique of VSS adaptive robust control theory. That is, we propose a VSS adaptive observer and a sliding mode control incorporated with this observer. We can prove the robust stability of the closed system applying the Lyapunov's second method.

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Robust Adaptive Output Feedback Control Design for a Multi-Input Multi-Output Aeroelastic System

  • Wang, Z.;Behal, A.;Marzocca, P.
    • International Journal of Aeronautical and Space Sciences
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    • v.12 no.2
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    • pp.179-189
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    • 2011
  • In this paper, robust adaptive control design problem is addressed for a class of parametrically uncertain aeroelastic systems. A full-state robust adaptive controller was designed to suppress aeroelastic vibrations of a nonlinear wing section. The design used leading and trailing edge control actuations. The full state feedback (FSFB) control yielded a global uniformly ultimately bounded result for two-axis vibration suppression. The pitching and plunging displacements were measurable; however, the pitching and plunging rates were not measurable. Thus, a high gain observer was used to modify the FSFB control design to become an output feedback (OFB) design while the stability analysis for the OFB control law was presented. Simulation results demonstrate the efficacy of the multi-input multi-output control toward suppressing aeroelastic vibrations and limit cycle oscillations occurring in pre- and post-flutter velocity regimes.

Design of the Combined Direct and Indirect Adaptive Neural Controller Using Fuzzy Rule (퍼지규칙에 의한 직.간접 혼합 신경망 적응제어시스템의 설계)

  • 이순영;장순용
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.3
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    • pp.603-610
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    • 2000
  • In this paper, the direct and indirect adaptive controller are combined based on the Lyapunov synthesis approach. The Proposed controller is constructed from RBF Neural Network and weighting parameters are adjusted on-line according to some adaptation law. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. In the results, proposed controller has the main advantages of both the direct adaptive controller and the indirect adaptive controller. The effectiveness of the proposed control scheme is demonstrated through simulation results of control for one-link rigid robotics manipulator.

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