Adaptive Control of Nonlinear and Stochastic Systems

Abstract

Abstract : Significant progress was made in a number of aspects of nonlinear and stochastic systems. Important contributions in the adaptive control of finite state Markov chains under partial observations were solved, and significant progress was made along more general directions. A project in surveying the literature on the ergodic control problem for discrete-time controlled Markov processes was completed. This work presented a comprehensive account of the considerable research on this problem over the past three decades. Further extending this effort, we embarked on writing a research monograph entitled 'Ergodic Control of Markov Chains and Stochastic Games' intended for publication as a volume in the series of 'Applications of Mathematics' by Springer-Verglag. A controlled switching diffusion model was developed to study the hierarchical control of flexible manufacturing systems. This study led to significant results in optimal control of stochastic hybrid system in both the discounted and average cost cases. In the area of deterministic nonlinear systems, numerical aspect of approximation linearization were investigated.