Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control

Abstract

Direct modeling of white noise in stochastic systems.- Markovian representations of cyclostationary processes.- Parametriztions of linear stochastic systems.- Stochastic realization for approximate modeling.- Representation of inner products and stochastic realization.- On realization and identification of stochastic bilinear systems.- On stochastic partial differential equations. Results on approximations.- Developments in parameter bounding.- Recent progress in parallel stochastic approximations.- On the adaptive stabilization and ergodic behaviour of stochastic systems with jump-Markov parameters via nonlinear filtering.- Identification and adaptive control for ARMAX systems.- Some methods for the adaptive control of continuous time linear stochastic systems.- Strong approximation results in estimation and adaptive control.- Stochastic adaptive control: Results and perspective.- Information bounds, certainty equivalence and learning in asymptotically efficient adaptive control of time-invariant stochastic systems.- Stability of Markov chains on topological spaces with applications to adaptive control and time series analysis.