Control and State Estimation for Dynamical Network Systems with Complex Samplings

This book discusses control and state estimation for dynamical network systems with complex samplings,including passive and active sampling methods. It proposes design technologies for controllers and estimators and provides simulation results to demonstrate their effectiveness. The book covers various theories and methodologies and offers sufficient conditions for the existence of desired controllers and estimators. It is intended for researchers, professionals, and graduate students in control engineering and signal processing.

Format: Hardback
Length: 282 pages
Publication date: 14 September 2022
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the intricate challenges of control and state estimation for dynamical network systems, considering the effects of complex samplings induced by various network-related phenomena. It presents a series of control and state estimation problems addressed through the passive sampling approach, highlighting the impact of active sampling methods, such as event-based sampling, on control/estimation performance. Moreover, novel design technologies for controllers and estimators are proposed, backed by comprehensive simulation results to enhance understanding. By leveraging a diverse range of theories and methodologies, including Lyapunov function, linear matrix inequalities, and Kalman theory, the book establishes sufficient conditions for the existence of desired controllers and estimators, parameterized according to specific matrix inequalities or recursive matrix equations.

The book caters to researchers, professionals, and graduate students in the fields of control engineering and signal processing, offering a valuable resource for advancing knowledge and understanding in this domain.

Dimension: 234 x 156 (mm)
ISBN-13: 9781032309965