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This paper proposes a self-triggered model predictive control algorithm for a class of discrete-time Markov jump linear systems with parametric uncertainties. A dual-mode design framework is employed to guarantee the optimality, feasibility and robust stability. The online control law is obtained by minimising the worst case of a novel cost function, which contains a self-triggered mechanism. Finally, a numerical example verifies the effectiveness and resource-saving capacity of the developed approach.

Self-triggered model predictive control of discrete-time Markov jump linear systems