Abstract
Repetitive processes are a distinct class of 2D systems of both theoretic and practical interest. The robust H-infinity control problem for uncertain stochastic time-delay linear continuous repetitive processes is investigated in this paper. First, sufficient conditions are proposed in terms of stochastic Lyapunov stability theory, Ito differential rule and linear matrix inequality technology. The corresponding controller design is then cast into a convex optimization problem. Attention is focused on constructing an admissible controller, which guarantees that the closed-loop repetitive processes are mean-square asymptotically stable and have a prespecified H-infinity performance γ with respect to all energy-bounded input signals. A numerical example illustrates the effectiveness of the proposed design scheme.
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