Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control

P. E. Caines

ISBN 10: 3540541330 / ISBN 13: 9783540541332

Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 1991, 1991

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This item is printed on demand - Print on Demand Titel. Neuware -This book contains a collection of survey papers in the areas of modelling, estimation and adaptive control of stochastic systems describing recent efforts to develop a systematic and elegant theory of identification and adaptive control. It is meant to provide a fast introduction to some of the recent achievements. The book is intended for graduate students and researchers interested in statistical problems of control in general. Students in robotics and communication will also find it valuable. Readers are expected to be familiar with the fundamentals of probability theory and stochastic processes.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 412 pp. Englisch.

Codice articolo 9783540541332

Dati bibliografici

• Titolo: Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control
• Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 1991
• Data di pubblicazione: 1991
• Lingua: Inglese
• ISBN 10: 3540541330
• ISBN 13: 9783540541332
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 244 L x 170 A x 23 P (millimetri) 244 millimetri di larghezza per 170 millimetri di altezza per 23 millimetri di profondità
• Peso: 708 grammi

Descrizione articolo

Riassunto

This book contains a collection of survey papers in the areas of modelling, estimation and adaptive control of stochastic systems describing recent efforts to develop a systematic and elegant theory of identification and adaptive control. It is meant to provide a fast introduction to some of the recent achievements. The book is intended for graduate students and researchers interested in statistical problems of control in general. Students in robotics and communication will also find it valuable. Readers are expected to be familiar with the fundamentals of probability theory and stochastic processes.

Contenuti

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.