Relaxed dissipative control of nonhomogeneous Markovian jump fuzzy systems via stochastic nonquadratic stabilization approach
Nguyễn Thanh Bình, Sung Hyun Kim
Abstract
Based on the stochastic nonquadratic stabilization approach, this paper proposes a method for designing dissipative controllers for continuous-time nonhomogeneous Markovian jump fuzzy systems such that performance enhancement and computational complexity reduction are simultaneously accomplished. First, the underlying stabilization conditions are formulated in terms of parameterized matrix inequalities depending on fuzzy basis functions, as well as on their time derivatives, and on mode-transition rates. Then, using our relaxation techniques that can impose stricter constraints on time-varying parameters, the stabilization conditions are converted into linear matrix inequalities (LMIs) that are less conservative and have lower computational complexity. The validity of this approach is shown by two illustrative examples.