Chao Zhai – författare

This book highlights designs, implementations and applications of tracking differentiator (TD) algorithms. The real-time differentiation estimation of a given signal is of high importance in control science and engineering. A good differentiator shall have i) robustness against input noises and ii) exactness with a small phase delay. The book has three focuses:

The proposed TD solution and its successful real-life applications shall stimulate wide interests in different areas including power systems, railway transportations and aerospace industry, etc.

This book highlights cooperative coverage control approaches of multi-agent systems in uncertain environments and their applications in various fields. A novel theoretical formulation of multi-agent coverage is proposed to fulfill the coverage task via divide-and-conquer scheme. By taking workload partition and sweeping operations simultaneously, a distributed sweep coverage algorithm of multi-agent systems is developed to cooperatively complete the workload on the given region, and its input-to-state stability is guaranteed in theory. Moreover, the coverage performance is evaluated by estimating the error between the actual coverage time and the optimal time. Three application scenarios are presented to demonstrate the advantages of cooperative coverage control approaches in missile interception, intelligent transportation systems and environment monitoring, respectively.

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.