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Probabilistic control of Markov jump systems by scenario optimization approach

  • * Corresponding author: Yanyan YIN

    * Corresponding author: Yanyan YIN 
The first author is supported by NSFC grant 61503155.
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  • This paper addresses the new problem of probabilistic robust stabilization for uncertain stochastic systems by using scenario optimization approach, where the uncertainties are not assumed to be norm-bounded. State feedback controllers are designed to guarantee that the closed-loop system is robust probabilistic stable. The problem of designing the controller gains is formulated and solved as linear matrix inequality (LMI) constraints. Simulation results are presented to illustrate the correctness and usefulness of the controllers designed.

    Mathematics Subject Classification: Primary: 93E15, 58F17; Secondary: 93E03.


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  • Figure 1.  State trajectory of a-posteriori Monte-Carlo analysis

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