Synopsis
This book studies the important notion of controllability robustness for complex dynamical networks in the linear or linearized settings. Chapter 1 provides an overview of network controllability and controllability robustness, as well as some preliminaries and research problems. Chapter 2 introduces the basic concept and knowledge of network controllability, covering definitions, computational methods, and evaluation metrics. It explores key topological features of the controllability robustness. Chapter 3 analyzes the controllability robustness in complex networks, introducing key metrics, attack strategies, hierarchical attack methods, simulation criteria, and analytical models. Chapter 4 explores techniques for enhancing the controllability robustness, introducing robustness-oriented models, metaheuristic-based optimization, and an empirical necessary condition verified through extensive experiments. Chapter 5 examines data-driven approaches for evaluating the controllability robustness, focusing on input representation, model architecture, and output interpretation, from a machine learning-based approach. Chapter 6 introduces a framework for assessing and visualizing the controllability robustness enhancement potential, leveraging data-driven methods to deliver accurate predictions and interpretability at low computational cost. Finally, Chapter 7 reviews recent advancements, identifies key challenges, and outlines future directions in network controllability robustness studies.
About the Authors
Dr Yang Lou received the PhD degree from the Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China, in 2017. From 2017 to 2025, he held research and academic positions at City University of Hong Kong, Lingnan University, the University of Osaka, and National Yang Ming Chiao Tung University. He has been an Associate Professor at the Graduate School of Advanced Science and Engineering, Hiroshima University, Japan, since August 2025. He has authored more than fifty peer-reviewed papers published in prestigious IEEE Transactions and Magazines, as well as other top-tier journals and leading international conferences. He is a Senior Member of the IEEE and a Fellow of the Higher Education Academy. His research interests include network science, graph learning, and optimization.
Professor Lin Wang received her PhD degree in Control Theory from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences in 2009. She then joined Shanghai Jiao Tong University and has been a Professor at the university since late 2019. She serves as Vice Chair of the IFAC Technical Committee on Large Scale Complex Systems, Deputy Director of the Committee on Complex Networks and Complex Systems of the China Society for Industrial and Applied Mathematics, and a Board Member of the Systems Engineering Society of China. In 2021, she was honored as a Shanghai Shuguang Scholar. In 2025, she received the Top Talent of Shanghai Eastern Talent Program and the Youth Science and Technology Award from the Chinese Association of Automation. Her current research interests include networked system analysis, cooperative control of unmanned aerial vehicles, and scheduling optimization of large-scale swarms.
Professor Guanrong Chen received the MSc degree in Computer Science from Sun Yat-sen University, Guangzhou, China in 1981 and the PhD degree in Applied Mathematics from Texas A&M University, USA in 1987. Since year 2000, he has been a Chair Professor and the founding director of the "Centre for Complexity and Complex Networks" at City University of Hong Kong. He is now the Hong Kong Shun Hing Education and Charity Fund Chair Professor of Engineering. Professor Chen was elected Fellow of the IEEE in 1997, awarded the 2011 Euler Gold Medal from Russia, and conferred Honorary Doctor Degrees by the Saint Petersburg State University, Russia in 2011 and by the University of Le Harve Normandy, France in 2014. He has been a Member of the Academia Europaea since 2014, and a Member of the European Academy of Engineering and a Fellow of The World Academy of Sciences since 2015. He was selected Fellow of the International Network Science Society in 2025. His research interests are in the fields of complex networks, nonlinear dynamics and control systems. He has been a Highly Cited Researcher for over a decade.
"About this title" may belong to another edition of this title.
