Hongjing Liang – författare

This book focuses on the characteristics of cooperative control problems for general linear multi-agent systems, including formation control, air traffic control, rendezvous, foraging, role assignment, and cooperative search. On this basis and combined with linear system theory, it introduces readers to the cooperative tracking problem for identical continuous-time multi-agent systems under state-coupled dynamics; the cooperative output regulation for heterogeneous multi-agent systems; and the optimal output regulation for model-free multi-agent systems. In closing, the results are extended to multiple leaders, and cooperative containment control for uncertain multi-agent systems is addressed. Given its scope, the book offers an essential reference guide for researchers and designers of multi-agent systems, as well as a valuable resource for upper-level undergraduate and graduate students.

This book focuses on the characteristics of cooperative control problems for general linear multi-agent systems, including formation control, air traffic control, rendezvous, foraging, role assignment, and cooperative search. On this basis and combined with linear system theory, it introduces readers to the cooperative tracking problem for identical continuous-time multi-agent systems under state-coupled dynamics; the cooperative output regulation for heterogeneous multi-agent systems; and the optimal output regulation for model-free multi-agent systems. In closing, the results are extended to multiple leaders, and cooperative containment control for uncertain multi-agent systems is addressed. Given its scope, the book offers an essential reference guide for researchers and designers of multi-agent systems, as well as a valuable resource for upper-level undergraduate and graduate students.

This book constitutes the refereed proceedings of the 4th International Conference on Neuromorphic Computing Chengdu, China, December 12–14, 2025.The 52 papers included in these proceedings were carefully reviewed and selected from 134 submissions.ICNC 2025 aimed to establish a high-level international platform for academic exchange, promoting the development and collaboration within the advanced interdisciplinary field of neuromorphic computing. The focus of the event covered a wide range of hot topics, including neuromorphic chip design and mod eling, brain-inspired computing architectures, low-power intelligent computing, neural network algorithms and applications, human-computer interaction andneurocognitive science.

This book constitutes the refereed proceedings of the 4th International Conference on Neuromorphic Computing Chengdu, China, December 12–14, 2025.The 52 papers included in these proceedings were carefully reviewed and selected from 134 submissions.ICNC 2025 aimed to establish a high-level international platform for academic exchange, promoting the development and collaboration within the advanced interdisciplinary field of neuromorphic computing. The focus of the event covered a wide range of hot topics, including neuromorphic chip design and mod eling, brain-inspired computing architectures, low-power intelligent computing, neural network algorithms and applications, human-computer interaction andneurocognitive science.

Integrating the adaptive learning control, backstepping technology, and event-triggered mechanism, this book solve the problems of the strong nonlinearity, complex constraints and uncertainties that traditional methods cannot handle. This book breaks through the traditional control's reliance on mathematical model accuracy, providing more robust solutions for engineering scenarios such as unmanned systems and smart grids. This book provides a comprehensive constraint control theoretical framework for nonlinear multiagent systems, which provides modular design ideas for readers to flexibly apply. We provide the comparison tables to present the performance differences in convergence speed, robustness, and other indicators between traditional methods and methods in this book. This book shows how to integrate classic control with modern intelligent technologies such as adaptive learning and event-triggered, providing interdisciplinary ideas for readers to solve complex system problems. Studies on event-triggered control and constrain control have attracted academic researchers an engineers from various disciplines, such as electrical, computer science, mathematics,physics, and mechanical.The target audience of this book includes graduate students in artificial intelligence and related fields, technology workers in the field of intelligent control, and academic researchers interested in collaborative control of multiagent systems, event-triggered control, and constraint control.