Studies in Systems, Decision and Control680- Complex Networks Control Theory

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Bol This book explores the intersection of control theory and complex network science through the framework of structural controllability of complex networks. This book explores the intersection of control theory and complex network science through the framework of structural controllability of complex networks. It introduces the main concepts, mathematical formulations, and computational algorithms needed to analyze the controllability of large-scale networked systems. Covering topics from basic control theory and graph-based methods to mathematical models and data-driven approaches, the book describes current applications of network controllability in social, engineering, and biological systems, with particular emphasis on biological networks. It thus offers an interdisciplinary view of a rapidly developing research area and highlights the growing importance of controllability analysis in complex real-world systems. It will be useful to researchers and graduate students in network science, systems biology, control theory, robotics, and related areas of engineering.

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This book explores the intersection of control theory and complex network science through the framework of structural controllability of complex networks. This book explores the intersection of control theory and complex network science through the framework of structural controllability of complex networks. It introduces the main concepts, mathematical formulations, and computational algorithms needed to analyze the controllability of large-scale networked systems. Covering topics from basic control theory and graph-based methods to mathematical models and data-driven approaches, the book describes current applications of network controllability in social, engineering, and biological systems, with particular emphasis on biological networks. It thus offers an interdisciplinary view of a rapidly developing research area and highlights the growing importance of controllability analysis in complex real-world systems. It will be useful to researchers and graduate students in network science, systems biology, control theory, robotics, and related areas of engineering.


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