The LQ control problem, for Markovian jumps linear systems with horizon defined by stopping times

This paper deals with a stochastic optimal control problem involving discrete-time jump Markov linear systems. The jumps or changes between the system operation modes evolve according to an underlying Markov chain. In the model studied, the problem horizon is defined by a stopping time /spl tau/ which represents either, the occurrence of a fix number N of failures or repairs (T/sub N/), or the occurrence of a crucial failure event (/spl tau//sub /spl Delta//), after which the system is brought to a halt for maintenance. In addition, an intermediary mixed case for which /spl tau/ represents the minimum between T/sub N/ and /spl tau//sub /spl Delta// is also considered. These stopping times coincide with some of the jump times of the Markov state and the information available allows the reconfiguration of the control action at each jump time, in the form of a linear feedback gain. The solution for the linear quadratic problem with complete Markov state observation is presented. The solution is given in terms of recursions of a set of algebraic Riccati equations (ARE) or a coupled set of algebraic Riccati equation (CARE).