Variance-Constrained Multi-Objective Stochastic Control and Filtering (Wiley Series in Dynamics and Control of Electromechanical Systems) - Hardcover

Ma, Lifeng; Wang, Zidong; Bo, Yuming

Hardcover

ISBN 10: 1118929497 ISBN 13: 9781118929490

Publisher: Wiley, 2015

Synopsis

• Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena
• Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance
• Includes case studies of several nonlinear stochastic systems
• Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations
• Considers both time-invariant systems and time-varying systems
• Exploits newly developed techniques to handle the emerging mathematical and computational challenges

About this title

About the Author

Lifeng Ma received the Ph.D. degree in Control Science and Engineering in 2010 from Nanjing University of Science and Technology, Nanjing, China. From August 2008 to February 2009, he was a Visiting Scholar in the Department of Information Systems and Computing, Brunel University, London, UK. From January 2010 to March 2010 and from May 2011 to September 2011, he was a Research Associate in the Department of Mechanical Engineering, the University of Hong Kong. He is now a Lecturer with the School of Automation, Nanjing University of Science and Technology, Nanjing, China. Dr. Ma's current research interests include nonlinear control and stochastic control. He is a very active reviewer for many international journals.

Zidong Wang is currently Professor of Dynamical Systems and Computing in the Department of Information Systems and Computing, Brunel University, UK. From 1990 to 2002, he held teaching and research appointments in universities in China, Germany and the UK. Prof. Wang's research interests include dynamical systems, signal processing, bioinformatics, control theory and applications. He has published more than 280 papers in refereed international journals. He is a holder of the Alexander von Humboldt Research Fellowship of Germany, the JSPS Research Fellowship of Japan, William Mong Visiting Research Fellowship of Hong Kong. He serves as the Executive Editor for Systems Science and Control Engineering (Taylor and Francis) and an Associate Editor for 11 international journals including five IEEE Transactions. Prof. Wang is a Fellow of the IEEE, a Fellow of the Royal Statistical Society and a member of the program committee for many international conferences.

Yuming Bo received his BSc degree in Automatic Control in 1984, his MSc degree in Automatic Control in 1987 and PhD degree in Control Theory and Control Engineering in 2005, all from Nanjing University of Science and Technology, Nanjing, China. He is now a Professor of Control Theory and Control Engineering in the School of Automation at Nanjing University of Science and Technology, Nanjing, China. His research interests include stochastic control and estimation, computer communication and programming. He has published more than 20 papers in refereed journals and served as an associate editor for two journals.

From the Back Cover

Variance-Constrained Multi-Objective Stochastic Control and Filtering
Lifeng Ma - Nanjing University of Science and Technology, China
Zidong Wang - Brunel University, UK
Yuming Bo - Nanjing University of Science and Technology, China

In engineering practice, it is always desirable to design systems capable of meeting performance requirements such as stability, robustness, and reliability. However nonlinear and stochastic systems are more complex by nature, and with the ever-increasing degree of system complexity, multi-objective design with variance constraints has become a key research area.

Variance-Constrained Multi-Objective Stochastic Control and Filtering covers the latest research results and presents the state-of-the-art of control and filtering problems while taking multiple design objectives into consideration. It examines recent advances in control and filtering in the presence of incomplete information and discusses application potential in engineering practice. The reader will also benefit from the introduction of new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

Key features:

• Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance
• Includes case studies of several nonlinear stochastic systems

• Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations
• Considers both time-invariant systems and time-varying systems
• Exploits newly developed techniques to handle the emerging mathematical and computational challenges

Variance-Constrained Multi-Objective Stochastic Control and Filtering is a comprehensive reference for engineers dealing with control and filtering problems for nonlinear stochastic systems, and is also suitable as a textbook for senior undergraduate and graduate students in this area.

From the Inside Flap

Variance-Constrained Multi-Objective Stochastic Control and Filtering
Lifeng Ma - Nanjing University of Science and Technology, China
Zidong Wang - Brunel University, UK
Yuming Bo - Nanjing University of Science and Technology, China

In engineering practice, it is always desirable to design systems capable of meeting performance requirements such as stability, robustness, and reliability. However nonlinear and stochastic systems are more complex by nature, and with the ever-increasing degree of system complexity, multi-objective design with variance constraints has become a key research area.

Variance-Constrained Multi-Objective Stochastic Control and Filtering covers the latest research results and presents the state-of-the-art of control and filtering problems while taking multiple design objectives into consideration. It examines recent advances in control and filtering in the presence of incomplete information and discusses application potential in engineering practice. The reader will also benefit from the introduction of new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

Key features:

• Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance
• Includes case studies of several nonlinear stochastic systems

• Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations
• Considers both time-invariant systems and time-varying systems
• Exploits newly developed techniques to handle the emerging mathematical and computational challenges

Variance-Constrained Multi-Objective Stochastic Control and Filtering is a comprehensive reference for engineers dealing with control and filtering problems for nonlinear stochastic systems, and is also suitable as a textbook for senior undergraduate and graduate students in this area.

Edition details

• Publisher: Wiley
• Publication date: 2015
• Language: English
• ISBN 10: 1118929497
• ISBN 13: 9781118929490
• Binding: Hardcover
• Edition number: 1
• Number of pages: 336