Decentralized Control and Filtering provides a rigorous framework for examining the analysis, stability and control of large-scale systems, addressing the difficulties that arise because dimensionality, information structure constraints, parametric uncertainty and time-delays. This monograph serves three purposes: it reviews past methods and results from a contemporary perspective; it examines presents trends and approaches and to provide future possibilities; and it investigates robust, reliable and/or resilient decentralized design methods based on a framework of linear matrix inequalities. As well as providing an overview of large-scale systems theories from the past several decades, the author presents key modern concepts and efficient computational methods. Representative numerical examples, end-of-chapter problems, and typical system applications are included, and theoretical developments and practical applications of large-scale dynamical systems are discussed in depth.

From the Back Cover

Decentralized Systems with Design Constraints provides a rigorous framework for examining the analysis, stability and control of large-scale systems, and addressing the difficulties that arise because of dimensionality, information structure constraints, parametric uncertainty and time-delays.

The achievements of this monograph are three-fold. It:

� reviews past methods and results from a contemporary perspective;

� examines present trends and approaches to provide future possibilities; and

� investigates robust, reliable and/or resilient decentralized design methods based on a linear matrix inequalities framework.

As well as providing an overall assessment of large-scale systems theories over the past several decades, the author presents key related concepts and efficient computational methods. Representative numerical examples, end-of-chapter problems, and typical system applications are included, and theoretical developments and practical applications of large-scale (interconnected) dynamical systems are discussed in depth.

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