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This book provides a comprehensive presentation of classical and advanced topics in estimation and control of dynamical systems with an emphasis on stochastic control. Many aspects which are not easily found in a single text are provided, such as connections between control theory and mathematical finance, as well as differential games.
The book is self-contained and prioritizes concepts rather than full rigor, targeting scientists who want to use control theory in their research in applied mathematics, engineering, economics, and management science. Examples and exercises are included throughout, which will be useful for PhD courses and graduate courses in general.Dr. Alain Bensoussan is Lars Magnus Ericsson Chair at UT Dallas and Director of the International Center for Decision and Risk Analysis which develops risk management research as it pertains to large-investment industrial projects that involve new technologies, applications and markets. He is also Chair Professor at City University Hong Kong.
List of contents
Introduction.- State Representation of Linear Dynamical Systems.- Optimal Control of Linear Dynamical Systems.- Estimation Theory.- Further Techniques of Estimation.- Compliments on Probability Theory.- Filtering Theory in Continuous Time.- Stochastic Control of Linear Dynamic Systems with Full Information.- Stochastic Control of Linear Dynamical Systems with Partial Information.- Deterministic Optimal Control.- Stochastic Optimal Control.- Additional Results for BSDE.- Stochastic Control Problems in Finance.- Stochastic Control for Non-Markov Processes.- Principal Agent Control Problems.- Differential Games.- Stackelberg Differential Games.- Target Problems.
Summary
This book provides a comprehensive presentation of classical and advanced topics in estimation and control of dynamical systems with an emphasis on stochastic control. Many aspects which are not easily found in a single text are provided, such as connections between control theory and mathematical finance, as well as differential games.
The book is self-contained and prioritizes concepts rather than full rigor, targeting scientists who want to use control theory in their research in applied mathematics, engineering, economics, and management science. Examples and exercises are included throughout, which will be useful for PhD courses and graduate courses in general.Dr. Alain Bensoussan is Lars Magnus Ericsson Chair at UT Dallas and Director of the International Center for Decision and Risk Analysis which develops risk management research as it pertains to large-investment industrial projects that involve new technologies, applications and markets. He is also Chair Professor at City University Hong Kong.
Additional text
“This book is a great resource for graduate students and those who want to learn and understand stochastic control theory. It is also a great read for experts who want to gain a broader overview of the subject and wish to see connections between different techniques. … this is an excellent book and a great complement to the current offering in stochastic control.” (Jan Palczewski, SIAM Review, Vol. 62 (1), 2020)
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"This book is a great resource for graduate students and those who want to learn and understand stochastic control theory. It is also a great read for experts who want to gain a broader overview of the subject and wish to see connections between different techniques. ... this is an excellent book and a great complement to the current offering in stochastic control." (Jan Palczewski, SIAM Review, Vol. 62 (1), 2020)
