Control And Optimization Methods For Complex System Resilience
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Control and Optimization Methods for Complex System Resilience
This book provides a systematic framework to enhance the ability of complex dynamical systems in risk identification, security assessment, system protection, and recovery with the assistance of advanced control and optimization technologies. By treating external disturbances as control inputs, optimal control approach is employed to identify disruptive disturbances, and online security assessment is conducted with Gaussian process and converse Lyapunov function. Model predictive approach and distributed optimization strategy are adopted to protect the complex system against critical contingencies. Moreover, the reinforcement learning method ensures the efficient restoration of complex systems from severe disruptions. This book is meant to be read and studied by researchers and graduates. It offers unique insights and practical methodology into designing and analyzing complex dynamical systems for resilience elevation.
Control and Optimization Methods for Complex System Resilience
This book provides a systematic framework to enhance the ability of complex dynamical systems in risk identification, security assessment, system protection, and recovery with the assistance of advanced control and optimization technologies. By treating external disturbances as control inputs, optimal control approach is employed to identify disruptive disturbances, and online security assessment is conducted with Gaussian process and converse Lyapunov function. Model predictive approach and distributed optimization strategy are adopted to protect the complex system against critical contingencies. Moreover, the reinforcement learning method ensures the efficient restoration of complex systems from severe disruptions. This book is meant to be read and studied by researchers and graduates. It offers unique insights and practical methodology into designing and analyzing complex dynamical systems for resilience elevation.
Models and Methods for Systems Engineering
This book compiles high-quality research contributions from leading experts, providing both theoretical foundations and practical methodologies that are shaping the future of engineering systems. In an era where technological innovation drives every industry, this book offers a comprehensive exploration of cutting-edge approaches in systems optimization, artificial intelligence, and digital transformation. Divided into three distinct sections—Advanced Technologies in Control, Optimization, and Communication Systems; Artificial Intelligence, Machine Learning, and Cybersecurity; and Human-Computer Interaction, Digital Transformation, and Future Internet Technologies—this book covers a wide range of topics essential for today’s engineers and researchers. From the latest advancements in spacecraft orbit control and energy-efficient IoT data management to groundbreaking work in medical diagnostics using AI, the book delivers a diverse array of applications across industries. This book is an invaluable resource for scientists, engineers, IT specialists, and students seeking to understand the complexities and opportunities in modern systems engineering. Whether you are a researcher looking for state-of-the-art techniques or a professional seeking practical solutions for engineering challenges, this book is designed to equip you with the tools and knowledge to succeed in a rapidly evolving field. Discover how the latest models and methods in systems engineering are reshaping technology and driving innovation across industries. This essential guide is perfect for professionals in fields such as computational intelligence, control engineering, artificial intelligence, signal processing, and digital transformation. It also serves as a robust reference for academic researchers, and students involved in engineering and applied science disciplines.