RECEDING HORIZON FINITE MEMORY CONTROL FOR MARKOV JUMP SYSTEMS
Markov跳变系统滚动时域有限记忆控制

This paper is concerned with the problem of receding horizon finite memory control (RHFMC) for discrete-time Markov jump linear systems. The aim is to find an output feedback control with a finite memory structure which can be represented by linear combination of outputs and inputs during a finite filter horizon. First, RHFMC with an iterative form is obtained while minimizing a quadratic performance index defined on a finite control horizon under an unbiased condition. Due to the difficulty of stability guarantee, then the above mentioned RHFMC is improved by determining terminal weighting matrix which satisfies cost monotonicitycondition. The control law calculated by using this kind of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality (LMI) form. Finally, anumerical example is given to illustrate the effectiveness of the proposed method.