Chao Zhai received the Bachelor's degree in automation engineering from Henan University in 2007 and earned the Master's degree in control theory and control engineering from Huazhong University of Science and Technology in 2009. He received the Ph.D. degree in complex system and control from the Institute of Systems Science, Chinese Academy of Sciences, Beijing, China, in June 2013. From July 2013 to August 2015, he was a post-doctoral fellow at the University of Bristol, Bristol, UK. He is a full professor at the School of Automation, China University of Geosciences, Wuhan, China. His research interests include multi-agent cooperative control, resilient system, social motor coordination, and geohazard monitoring. He is a senior member of IEEE.

“The book is of considerable interest to specialists working in the field of stability theories and applications, in particular, the stability of power systems.” (Anatoly Martynyuk, zbMATH 1552.93001, 2025)

• Introduction to Complex System Resilience.- Optimal Control Approach to Identifying Cascading Failures.- Jacobian-free Newton-Krylov Method for Risk Identification.- Security Monitoring using Converse Lyapunov Function.- Online Gaussian Process Learning for Security Assessment.- Risk Identification of Cascading Process under Protection.- Model Predictive Approach to Preventing Cascading Process.- Robust Optimization Approach to Uncertain Cascading Process.- Cooperative Control Methods for Relieving System Stress.- Distributed Optimization Approach to System Protection.- Reinforcement Learning Approach to System Recovery.- Summary and Future Work.

Chao Zhai received the Bachelor's degree in automation engineering from Henan University in 2007 and earned the Master's degree in control theory and control engineering from Huazhong University of Science and Technology in 2009. He received the Ph.D. degree in complex system and control from the Institute of Systems Science, Chinese Academy of Sciences, Beijing, China, in June 2013. From July 2013 to August 2015, he was a post-doctoral fellow at the University of Bristol, Bristol, UK. He is a full professor at the School of Automation, China University of Geosciences, Wuhan, China. His research interests include multi-agent cooperative control, resilient system, social motor coordination, and geohazard monitoring. He is a senior member of IEEE.

“The book is of considerable interest to specialists working in the field of stability theories and applications, in particular, the stability of power systems.” (Anatoly Martynyuk, zbMATH 1552.93001, 2025)

• Introduction to Complex System Resilience.- Optimal Control Approach to Identifying Cascading Failures.- Jacobian-free Newton-Krylov Method for Risk Identification.- Security Monitoring using Converse Lyapunov Function.- Online Gaussian Process Learning for Security Assessment.- Risk Identification of Cascading Process under Protection.- Model Predictive Approach to Preventing Cascading Process.- Robust Optimization Approach to Uncertain Cascading Process.- Cooperative Control Methods for Relieving System Stress.- Distributed Optimization Approach to System Protection.- Reinforcement Learning Approach to System Recovery.- Summary and Future Work.

Chao Zhai received the Bachelor's degree in automation engineering from Henan University in 2007 and earned the Master's degree in control theory and control engineering from Huazhong University of Science and Technology in 2009. He received the Ph.D. degree in complex system and control from the Institute of Systems Science, Chinese Academy of Sciences, Beijing, China, in June 2013. From July 2013 to August 2015, he was a post-doctoral fellow at the University of Bristol, Bristol, UK. He is a full professor at the School of Automation, China University of Geosciences, Wuhan, China. His research interests include multi-agent cooperative control, resilient system, social motor coordination, and geohazard monitoring. He is a senior member of IEEE.

“The book is of considerable interest to specialists working in the field of stability theories and applications, in particular, the stability of power systems.” (Anatoly Martynyuk, zbMATH 1552.93001, 2025)

• Introduction to Complex System Resilience.- Optimal Control Approach to Identifying Cascading Failures.- Jacobian-free Newton-Krylov Method for Risk Identification.- Security Monitoring using Converse Lyapunov Function.- Online Gaussian Process Learning for Security Assessment.- Risk Identification of Cascading Process under Protection.- Model Predictive Approach to Preventing Cascading Process.- Robust Optimization Approach to Uncertain Cascading Process.- Cooperative Control Methods for Relieving System Stress.- Distributed Optimization Approach to System Protection.- Reinforcement Learning Approach to System Recovery.- Summary and Future Work.