
Finite-Time Control of Networked Systems by Xinsong Yang
This book mainly provides recent advances in finite-time and fixed-time control issues for complex networks and neural networks. It is well known that finite-time techniques have more advantages over asymptotical ones. Besides fast convergence rates, finite-time techniques have better robustness and disturbance rejection properties. However, it is challenging to deal with time delay in studying finite-time control. For readers’ easy understanding, the finite-time control issue for systems with and without time delays is separately introduced in this book. Moreover, the issues of finite-time and fixed-time control for differential equations with discontinuous states on the right-hand side are also considered. Many interesting results concerning finite-time and fixed-time synchronization are provided in the form of lemmas, theorems, or corollaries, accompanied by systematic theoretical analysis for the proof of their sufficient conditions, controller design, and new analysis techniques. Each new result is verified by at least one numerical example with detailed data analysis. Therefore, this book is an advantageous tool and is beneficial for interested experts and scholars in the control field.
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Set Theory-Based Spacecraft Dynamics and Control
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Data-Driven Spatiotemporal Modeling and Control of Nonlinear Distributed Parameter Systems and Their Applications
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Robust Adaptive Control of Nonlinear Interconnected Systems with Input Nonlinearities and Faults
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Constrained Cooperation: Event-Triggered and Intelligent Backstepping Control for Nonlinear Multiagent Systems
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Disagreement Behavior Analysis of Signed Networks
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Strict-Feedback Nonlinear Systems
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Variable Gain Design in Stochastic Iterative Learning Control
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Iterative Learning Control for Network Systems Under Constrained Information Communication
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Discrete-Time Adaptive Iterative Learning Control
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Complex-Valued Neural Networks Systems with Time Delay
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Data-Driven Fault Detection and Reasoning for Industrial Monitoring
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Distributed Fault-Tolerant Consensus Control of Leader-Following Systems
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Variance-Constrained Filtering for Stochastic Complex Systems
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Analysis and Design of Delayed Neural Networks
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Distributed Impulsive Coordination of Multi-Agent Systems
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Fault Diagnosis and Fault-Tolerant Control of Nonlinear Systems with Higher System Input Powers
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Intelligent Control of Nonlinear Systems and Nonlinear Multi-Agent Systems with Complex Constraints
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Adaptive Collaborative Control of Multiagent Systems by Event-Triggered Mechanisms
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Fault-Tolerant Control for Time-Varying Delayed T-S Fuzzy Systems
Xinsong Yang received the B.S. degree in mathematics from Huaihua Normal University, Huaihua, Hunan, China, in 1992, and the M.S. degree in mathematics from Yunnan University, Kunming, Yunnan, China, in 2006. From 2008 to 2009, he was a Visiting Scholar with the Department of Mathematics, Southeast University, Nanjing, China. In 2014, he was a Visiting Professor with the Department of Mathematics, City University of Hong Kong, Hong Kong, China. In 2015, he was a Research Fellow with the Department of Mechanical Engineering, The University of Hong Kong, Hong Kong. In 2016, he was a Research Fellow with the Department of Mathematics, The Hong Kong Polytechnic University, Hong Kong. From 2006 to 2012, he was with Honghe University, Honghe, Yunnan. From 2012 to 2020, he was a Professor with Chongqing Normal University, Chongqing, China. Since 2021, he has been a Professor with Sichuan University, Chengdu, Sichuan. He has authored or coauthored more than 100 papers in refereed international journals. His current research interests include collective behavior in complex dynamical networks, multiagent system, chaos synchronization, control theory, discontinuous dynamical systems, and neural networks. Prof. Yang serves as an Associate Editor for Neurocomputing, Neural Processing Letters, Mathematics, Frontiers in Applied Mathematics and Statistics, and Mathematical Modeling and Control. He was the Highly Cited Researcher by Thomson Reuters/Clarivate Analytics from 2019 to 2023.
Yaping Sun received the B.S. degree in agricultural mechanization and automation from Southwest University, Chongqing, China, in 2016, and the Ph.D. degree in control science and engineering with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China, in 2021. Since 2021, she has been a Full Postdoctoral Researcher with the College of Electronic and Information Engineering, Sichuan University, Chengdu, China. Her research interests lie in the areas of switched multi-agent coordination control theory and its applications to autonomous robotics, unmanned ground vehicles, and unmanned aerial vehicles.
Rongqiang Tang received the M.S. degree in applied mathematics from Chongqing Normal University, Chongqing, China, in 2018. He is currently pursuing the Ph.D. degree with Sichuan University, Chengdu, China. His research interests include collective behavior in complex dynamical systems, finite-time control, and switched systems.
Meijie Zhang received the B.S. degree in electronic and information engineering from the North University of China, Taiyuan, China, in 2021. She is currently pursuing the Ph.D. degree with the College of Electronic and Information Engineering, Sichuan University, Chengdu, China. Her current research interests include state estimation of complex switched networks, event-triggered control, and consensus of multi-agent systems.
| SKU | Unavailable |
| ISBN 13 | 9789819603275 |
| ISBN 10 | 9819603277 |
| Title | Finite-Time Control of Networked Systems |
| Author | Xinsong Yang |
| Series | Intelligent Control And Learning Systems |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2025-04-02 |
| Number of pages | 422 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |


















