Policy iteration-based adaptive optimal control for Markov jump systems: a transition-probability-free asynchronous approach

A policy iteration-based adaptive optimal control algorithm using a transition-probability-free asynchronous approach has been developed for a class of MJSs. This algorithm approximates the optimal CARE solution without requiring prior knowledge of the system matrices. By employing a constructed discounted cost function, the coupled transition probabilities are no longer necessary. Finally, the convergence of the proposed algorithm is verified.