PARALLEL RECURSIVE ALGORITHMS IN ASYMPTOTICALLY EFFICIENT ADAPTIVE-CONTROL OF LINEAR STOCHASTIC-SYSTEMS

First, a review of some recent developments in stochastic adaptive control of linear stochastic systems is given. By integrating and refining several basic ideas in these developments, a relatively complete asymptotic solution to the adaptive control problem is then provided for such systems. The solution involves parallel implementation of a few basic recursive identification algorithms that serve to complement each other. It also involves occasional use of a dither signal to probe the system for information.