• Title/Summary/Keyword: LPV model

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ROBUST CONTROLLER DESIGN FOR IMPROVING VEHICLE ROLL CONTROL

  • Du, H.;Zhang, N
    • International Journal of Automotive Technology
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    • v.8 no.4
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    • pp.445-453
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    • 2007
  • This paper presents a robust controller design approach for improving vehicle dynamic roll motion performance and guaranteeing the closed-loop system stability in spite of vehicle parameter variations resulting from aging elements, loading patterns, and driving conditions, etc. The designed controller is linear parameter-varying (LPV) in terms of the time-varying parameters; its control objective is to minimise the $H_{\infty}$ performance from the steering input to the roll angle while satisfying the closed-loop pole placement constraint such that the optimal dynamic roll motion performance is achieved and robust stability is guaranteed. The sufficient conditions for designing such a controller are given as a finite number of linear matrix inequalities (LMIs). Numerical simulation using the three-degree-of-freedom (3-DOF) yaw-roll vehicle model is presented. It shows that the designed controller can effectively improve the vehicle dynamic roll angle response during J-turn or fishhook maneuver when the vehicle's forward velocity and the roll stiffness are varied significantly.

Nonlinear Adaptive Control Law for ALFLEX Using Dynamic Inversion and Disturbance Accommodation Control Observer

  • Higashi, Daisaku;Shimada, Yuzo;Uchiyama, Kenji
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1871-1876
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    • 2005
  • In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.

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An Adaptive Flight Control Law Design for the ALFLEX Flight Control System

  • Imai, Kanta;Shimada, Yuzo;Uchiyama, Kenji
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.148.5-148
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    • 2001
  • In this report, an adaptive flight control law based on a linear-parameter-varying (LPV) model is presented for a flight control system. The control system is designed to track an output of a vehicle to a reference signal from the guidance system, which generates a reference flight path. The proposed adaptive control law adjusts the controller gains continuously on line as flight conditions change. The obtained adaptive controller guarantees global stability over a wide flight envelope. Computer simulation involving six-degree-of-freedom nonlinear flight dynamics is applied to Japan´s automatic landing flight experimental vehicle (ALFLEX) to examine the effectiveness of the proposed adaptive flight control law.

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Robust Gain Scheduling Based on Fuzzy Logic Control and LMI Methods (퍼지논리제어와 LMI기법을 이용한 강인 게인 스케줄링)

  • Chi, Hyo-Seon;Koo, Kuen-Mo;Lee, Hungu;Tahk, Min-Jea;Hong, Sung-Kyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.1
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    • pp.1162-1170
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    • 2001
  • This paper proposes a practical gain-scheduling control law considering robust stability and performance of Linear Parameter Varying(LPV) systems in the presence of nonlinearities and uncertainties. The proposed method introduces LMI-based pole placement synthesis and also associates with a recently developed fuzzy control system based on Takagei-Sugenos fuzzy model. The sufficient conditions for robust controller design of linearized local dynamics and robust stabilization of fuzzy control systems are reduced to a finite set of Linear Matrix inequalities(LMIs) and solved by using co-evolutionary algorithms. The proposed method is applied to the longitudinal acceleration control of high performance aircraft with linear and nonlinear simulations.

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