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CAO Qi-min, ZHANG Yan-xia. Adaptive switching control of a class of nonlinear systems based on mixed multiple models[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2012, 21(4): 504-509.
Citation: CAO Qi-min, ZHANG Yan-xia. Adaptive switching control of a class of nonlinear systems based on mixed multiple models[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2012, 21(4): 504-509.
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Adaptive switching control of a class of nonlinear systems based on mixed multiple models

  • 1.

    School of Automation, Beijing Institute of Technology, Beijing 100081, China

  • 2.

    School of Mathematics, Beijing Institute of Technology, Beijing 100081, China

  • Received Date:2011-10-20
    Abstract
  • The transient behaviors of traditional adaptive control may be very poor in general. A practically feasible approach to improve the transient performances is the adoption of adaptive switching control. For a typical class of nonlinear systems disturbed by random noises, mixed multiple models consisting of adaptive model and fixed models were considered to design the switching control law. Under certain assumptions, the nonlinear system with the switching control law was proved rigorously to be stable and optimal. A simulation example was provided to compare the performance of the switching control and the traditional adaptive control.
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    • References (23)
  • [1]
    Morse A S. Supervisory control of families of linear set-point controls-part Ⅰ: exact matching[J]. IEEE Transaction on Automatic Control, 1996, 41:1413-1431.
    [2]
    Morse A S. Supervisory control of families of linear set-point controls-part Ⅱ: exact matching[J]. IEEE Transaction on Automatic Control, 1997,42:1500-1515.
    [3]
    Huang C L. Robust discrete variable structure control with finite-time approach to switching surface[J]. Automatica, 2002, 38:167-175.
    [4]
    Lainiotis D G. Partitioning: a unifying framework for adaptive systems, Part I and Ⅱ[J]. Proceeding of the IEEE, 1976, 64:Part Ⅰ,1126-1142; Part Ⅱ, 1182-1197.
    [5]
    Magill D T. Optimal adaptive estimations of sampled stochastic process[J]. IEEE Transaction on Automatic Control, 1965, AC-10:434-439.
    [6]
    Narendra K S, Balakrishnan J. Adaptive control using multiple models and switching[J]. IEEE Transaction on Automatic Control, 1997,42:171-187.
    [7]
    Narendra K S, Cheng Xiang. Adaptive control of discrete-time systems using multiple models[J]. IEEE Transaction on Automatic Control, 2000,45:1669-1686.
    [8]
    Athans M, Castanon D, Dunn K, et al. The stochastic control of the F-8c aircraft using a multiple model adaptive control(MMAC) method-Part Ⅰ: equilibrium flight[J]. IEEE Transaction on Automatic Control, 1977, AC-22: 768-780.
    [9]
    Maybeck P S , Pogoda D L. Multiple model adaptive controller for the stol f-15 with sensor/actuator failures //Proceeding of 28th IEEE Conference on Decision Control. New York: IEEE, 1989:1566-1572.
    [10]
    Moose R L, Van Landingham H F, McCabe D H. Modeling and estimation for tracking maneuvering targets [J]. IEEE Transaction on Aerospace and Electronic System, 1979, AES-15:448-456.
    [11]
    Kan R. Adaptive switching control of discrete time nonlinear systems based on multiple models[J]. Journal of Control Theory and Applications,2004,2: 43-50.
    [12]
    Zhang Y, Guo L. Stochastic adaptive switching control based on multiple models [J]. Journal of Systems Science and Complexity, 2002,15(1):18-34.
    [13]
    Cheng D, Guo L, Lin Y, et al. Stabilization of switched linear systems[J]. IEEE Transaction on Automatic Control,2005, 50(5):661-666.
    [14]
    Liu F, Song Y D, Tang T. Stabilization of switched linear systems with sampled feedback controller and bounded disturbance //29th Chinese Control Conference (CCC). Beijing: Technical Committee on Control Theory, 2010: 2254-2257.
    [15]
    Ma H. Finite-model adaptive control using WLS-like algorithm[J]. Automatica,2007, 43(4):677-684.
    [16]
    Ma H. Finite-model adaptive control using LS-like algorithm[J].International Journal of Adaptive Control and Signal Processing,2007, 21(5):391-414.
    [17]
    Ma H. Several algorithms for finite-model adaptive control problem[J]. Mathematics of Control,Signals,and Systems,2008,20(3):271-303.
    [18]
    Anderson B D O, Brinsmead T, Bruyne F D, et al. Multiple model adaptive control. Part Ⅰ: finite controller coverings[J]. International Journal of Robust and Nonlinear Control, 2000, 10(11-12):909-929.
    [19]
    Hespanha J P, Liberzon D, Morse A S, et al. Multiple model adaptive control, part 2: switching[J]. International Journal of Robust and Nonlinear Control, 2001,11(5):479-496.
    [20]
    Guo L, Chen H F. The ström-Wittenmark self-tuning regulator revisited and ELS-based adaptive trackers[J]. IEEE Transaction on Automatic Control, 1991, 36(7):802-812.
    [21]
    Guo L, Cheng D Z, Feng D X, et al. Control theory introduction[M]. Beijing: Science Press, 2005.
    [22]
    Guo L. Self-convergence of weighted least-squares with applications to stochastic adaptive control[J]. IEEE Transaction on Automatic Control, 1996, 41(1):79-89.
    [23]
    Guo L. Further results on least squares based adaptive minimum variance control[J]. SIAM Journal on Control and Optimization, 1994, 32(1):187-211.
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