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    Constrained model predictive control on convex polyhedron stochastic linear parameter varying systems

    Access Status
    Fulltext not available
    Authors
    Yin, YanYan
    Shi, Y.
    Liu, F.
    Date
    2013
    Type
    Journal Article
    
    Metadata
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    Citation
    Yin, Y. and Shi, Y. and Liu, F. 2013. Constrained model predictive control on convex polyhedron stochastic linear parameter varying systems. International Journal of Innovative Computing, Information and Control. 9 (10): pp. 4193-4204.
    Source Title
    International Journal of Innovative Computing, Information and Control
    ISSN
    1349-4198
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/52671
    Collection
    • Curtin Research Publications
    Abstract

    The problem of constrained model predictive control on a class of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficient matrices for the time variant system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic system, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon, stability of the system is guaranteed by searching a state feedback control law. Finally, constraints on both inputs and outputs are considered for such system and predictive controller is designed in terms of linear matrix inequality. Simulation example shows the validity of this method. © ISSN 1349-4198.

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