IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 2006 · 304 citations · 29 references
EngineeringDecision SciencesProcess ControlStochastic ModelingUncertainty QuantificationControl SystemsControl TheoryController DesignRobust ControlStabilityStochastic StabilityFuzzy ControlLyapunov FunctionsMarkov Jump SystemsNonlinear System ModelingRobust Control Of Uncertain SystemsRobust StabilizationStabilizationStochastic Lyapunov Functions
This paper is concerned with the robust-stabilization problem of uncertain Markovian jump nonlinear systems (MJNSs) without mode observations via a fuzzy-control approach. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. The aim is to design a mode-independent fuzzy controller such that the closed-loop Markovian jump fuzzy system (MJFS) is robustly stochastically stable. Based on a stochastic Lyapunov function, a robust-stabilization condition using a mode-independent fuzzy controller is derived for the uncertain MJFS in terms of linear matrix inequalities (LMIs). A new improved LMI formulation is used to alleviate the interrelation between the stochastic Lyapunov matrix and the system matrices containing controller variables in the derivation process. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.
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