• Title/Summary/Keyword: Uncertain Nonlinear Systems

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Robust Backstepping Control for Nonvanishing Parametrization$^1$

  • Shim, Hyung-Bo;Son, Young-Ik;Lee, Sang-Hyuk;Seo, Jin-Heon
    • Journal of KIEE
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    • v.10 no.1
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    • pp.29-34
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    • 2000
  • In this paper, a design method of a controller is presented for a class of nonlinear systems which have time-varying parametric uncertainly. Some features of this controller are that it can tackle 1) nonlinear parametrization(i.e. uncertain parameters enter the system in the nonlinear form) and 2) nonvanishing peturbation (i.e. uncertainty need not vanish at the origin). The class of systems considered in this paper has the triangular structure for which the well-known backstepping design can be applied. The uncertain parameter is assumed to be contained in the bounded set whose size can be arbitrarily large. Also, the uncertain system are globally uniformly bounded and converge to a compact set whose size is designable. In particular, the first state of the system can be made arbitrarily small, which can be seen by the presented simulation result.

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An LMI Approach to Nonlinear Sliding Surface Design (비선형 슬라이딩 평면의 설계를 위한 LMI 접근법)

  • Choi, Han-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.12
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    • pp.1197-1200
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    • 2010
  • The problem of designing a nonlinear sliding surface for an uncertain system is considered. The proposed sliding surface comprises a linear time invariant term and an additional time varying nonlinear term. It is assumed that a linear sliding surface parameter matrix guaranteeing the asymptotic stability of the sliding mode dynamics is given. The linear sliding surface parameter matrix is used for the linear term of the proposed sliding surface. The additional nonlinear term is designed so that a Lyapunov function decreases more rapidly. By including the additional nonlinear term to the linear sliding surface parameter matrix we obtain a nonlinear sliding surface such that the speed of responses is improved. We also give a switching feedback control law inducing a stable sliding motion in finite time. Finally, we give an LMI-based design algorithm, together with a design example.

Output-Feedback Control of Uncertain Nonlinear Systems Using Adaptive Fuzzy Observer with Minimal Dynamic Order

  • Park, Jang-Hyun;Huh, Sung-Hoe;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.39.2-39
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    • 2001
  • This paper describes the design of an output-feedback controller based on an adaptive fuzzy observer for uncertain single-input single-output nonlinear dynamical systems. Especially, we have focused on the realization of minimal dynamic order of the adaptive fuzzy observer. For the purpose, we propose a new method in which no strictly positive real(SPR) condition is needed and combine dynamic rule activation scheme with on-line estimation of fuzzy parameters. By using proposed scheme, we can reduce computation time, storage space, and dynamic order of the adaptive fuzzy observer ...

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Guaranteed Cost Control for Uncertain Time-Delay Systems with nonlinear Perturbations via Delayed Feedback (지연귀환을 통한 비선형 섭동이 존재하는 불확실 시간지연 시스템의 성능보장 제어)

  • Park, Ju-Hyun;Kwon, Oh-Min
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.6
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    • pp.581-588
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    • 2007
  • In this paper, we propose a delayed feedback guaranteed cost controller design method for linear time-delay systems with norm-bounded parameter uncertainties and nonlinear perturbations. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, an LMI optimization problem is formulated to design a controller such that the closed-loop cost function value is not more than a specified upper bound for all admissible system uncertainties and nonlinear perturbations. Numerical example show the effectiveness of the proposed method.

A Robust Adaptive Controller for Markovian Jump Uncertain Nonlinear Systems with Wiener Noises of Unknown Covariance

  • Zhu, Jin;Xi, Hong-Sheng;Ji, Hai-Bo;Wang, Bing
    • International Journal of Control, Automation, and Systems
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    • v.5 no.2
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    • pp.128-137
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    • 2007
  • A robust adaptive controller design for a class of Markovian jump parametric -strict-feedback systems is given. The disturbances considered herein include both uncertain nonlinearities and Wiener noises of unknown covariance. And they satisfy some bound-conditions. By using stochastic Lyapunov method in Markovian jump systems, a switching robust adaptive controller was obtained that guarantees global uniform ultimate boundedness of the closed-loop jump system.

Static Output Feedback Robust $H\infty$ Fuzzy Control of Discrete-Time Nonlinear Systems with Time-Varying Delay (시변 지연 이산 시간 비선형 시스템에 대한 정적 출력 궤환 $H\infty$ 퍼지 강인 제어기 설계)

  • Kim Taek Ryong;Park Jin Bae;Joo Young Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.04a
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    • pp.149-152
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    • 2005
  • In this paper, a robust $H\infty$ stabilization problem to a uncertain discrete-time fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi -Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H\infty$ controllers are given in terms of linear matrix inequalities.

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Self-Structuring Radial -Basis Function Network for Identification of Uncertain Nonlinear Systems

  • Jun, Jae-Choon;Park, Jang-Hyun;Yoon, Pil-Sang;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.26.6-26
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    • 2001
  • In this paper we introduce a new algorithm that enables radial basis function network(RBFN) to be structured automatically and guarantees the stability of the RBFN. Because this new algorithm is efficient and also have the advantage of fast computational speed we adopt this algorithm as online learning scheme for uncertain nonlinear dynamical systems. Based on the fact that a 3-layered RBFN can represent a specific nonlinear function reasonably well by linearly combining a set of nonlinear and localized basis functions, we show that this RBFN can identify the nonlinear system very well without knowing the information of the system in advance.

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A Balanced Model Reduction for Uncertain Nonlinear Systems (불확실한 비선형 시스템의 균형화된 모델축소)

  • Yoo, Seog-Hwan;Choi, Byung-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.144-149
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    • 2006
  • This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

East H$_{\infty}$ Gain Scheduling for Uncertain Nonlinear Systems

  • Lee, Seon-Ho;Lim, Jong-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.362-366
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    • 1998
  • This paper proposes a fast H$\sub$$\infty$/ gain scheduled controller that stabilizes the uncertain nonlinear system with exogenous signals. The controller is constructed at a distinct and fixed value of exogenous signals using H$\sub$$\infty$/ syn-thesis methodology. Then the constructed controller set is switched for the wide range of variation of exogenous signals. Using the derivative gain, the number of constructed and engaged controllers for the fast varying exogenous signal is reduced.

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Design of robust gain scheduling controllers in uncertain nonlinear systems

  • Lee, Seon-Ho;Lim, Jong-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.231-234
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    • 1996
  • This paper considers the output regulation problems on uncertain systems. Using NR-estimator(on-line), a family of equilibrium points for the uncertain system is computed. The state variables of the closed loop system track the average value of the obtained equilibrium manifold by dynamic state feedback control.

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