Control and decision strategy for a class of Markovian jump system with input constraints

The control and decision problem for a class of Markovian jump system with input constraints is investigated in this paper. The concerned system is composed of several subsystems where stochastic jump among the subsystems is described by a Markov chain, and constrained control performance of the considered system is thus deduced with the mode transition rate matrix (MTRM). By introducing decisions into MTRM, the traditional constrained control performance of Markovian jump system with input constraints is extended to a new hybrid one with decision cost as an addition. Based on this, a feasible control and decision strategy with the detailed algorithm is given for the minimization of the new hybrid performance. Comparisons are given considering the following cases: with/without input constraints, with/without decisions. And the efficiency of the proposed algorithm is verified by numerical simulations.