Minimum entropy control of closed-loop tracking errors for dynamic stochastic systems

Abstract

The entropy has been used to characterize the uncertainty of the tracking error for general nonlinear and non-Gaussian stochastic systems. A recursive optimization solution has been developed and the local stability condition of the closed-loop system has been established. The generality of this algorithm has been proved by the special case study of the minimum variance control for linear Gaussian systems.