Online Value Iteration for Intelligent Discounted Tracking Design of Constrained Systems

Abstract

In this brief, in order to solve the discounted optimal tracking control problem for discrete-time systems with control constraints, an advanced online value iteration (VI) algorithm is developed. First, we revisit discounted general value iteration (GVI) for optimal tracking control design. Second, the stability condition of GVI is established, which can be applied to evaluate the current iterative tracking control policy. Third, based on the concept of attraction domain, the evolving tracking control policies generated by online VI can be obtained through judging the location of the current tracking error. Finally, we prove system stability based on online VI for the present tracking control problem. A simulation example is shown to illustrate the effectiveness of the developed algorithm.