Details
Cooperative Coverage Control of Multi-Agent Systems and its Applications
Studies in Systems, Decision and Control, Band 408
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 07.12.2021 |
| ISBN/EAN: | 9789811676253 |
| Sprache: | englisch |
| Anzahl Seiten: | 139 |
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Beschreibungen
<p>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.</p>
<p>Introduction to Multi-Agent Cooperative Coverage Control.- Distributed Control Scheme for Online Workload Partition.- Decentralized Cooperative Sweep Coverage Algorithm in Uncertain Environments.- Adaptive Cooperative Coverage Algorithm with Online Learning Strategies.- Distributed Sweep Coverage Algorithm using Workload Memory.- Cooperative Sweep Coverage Algorithm of Discrete Time Multi-Agent Systems.- Coverage-Based Cooperative Interception against Supersonic Flight Vehicles.- Coverage-Based Cooperative Routing Algorithm for Unmanned Ground Vehicles.- Cooperative Coverage Control of Wireless Sensor Networks for Environment Monitoring.- Summary and Future Work.</p>
<p>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 Post-Doctoral Fellow with the University of Bristol, Bristol, UK. Currently, He is Professor at the School of Automation, China University of Geosciences, Wuhan, China. His research interests include cooperative control of multi-agent systems, power system resilience and social motor coordination. </p>
<p>Hai-Tao Zhang received the B.E. and Ph.D. degrees from the University of Science and Technology of China, Hefei, China, in 2000 and 2005, respectively. During January to December 2007, he was Postdoctoral Researcher with the University of Cambridge, Cambridge, UK. Currently, he is Full Professor with Huazhong University of Science and Technology, Wuhan, China. His research interests include swarming intelligence, model predictive control, and unmanned system cooperation control. He is a Cheung Kong Young Scholar. He is/was an associate editor of IEEE Transactions on Systems, Man and Cybernetics-Systems, IEEE Transactions on Circuits and Systems II and Asian Journal of Control. </p>
<p>Gaoxi Xiao received his Ph.D. degree in computing from the Hong Kong Polytechnic University. He joined the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, in 2001, where he is now Associate Professor. His main research interests include complex systems and complex networks, communication networks, smart grids, and system resilience and risk management. He serves/served as Associate Editor or Guest Editor for IEEE Transactions on Network Science and Engineering, PLOS ONE and Advances in Complex Systems, etc.</p><br>
<p>Hai-Tao Zhang received the B.E. and Ph.D. degrees from the University of Science and Technology of China, Hefei, China, in 2000 and 2005, respectively. During January to December 2007, he was Postdoctoral Researcher with the University of Cambridge, Cambridge, UK. Currently, he is Full Professor with Huazhong University of Science and Technology, Wuhan, China. His research interests include swarming intelligence, model predictive control, and unmanned system cooperation control. He is a Cheung Kong Young Scholar. He is/was an associate editor of IEEE Transactions on Systems, Man and Cybernetics-Systems, IEEE Transactions on Circuits and Systems II and Asian Journal of Control. </p>
<p>Gaoxi Xiao received his Ph.D. degree in computing from the Hong Kong Polytechnic University. He joined the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, in 2001, where he is now Associate Professor. His main research interests include complex systems and complex networks, communication networks, smart grids, and system resilience and risk management. He serves/served as Associate Editor or Guest Editor for IEEE Transactions on Network Science and Engineering, PLOS ONE and Advances in Complex Systems, etc.</p><br>
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.
Highlights cooperative coverage control approaches of multi-agent systems Presents a distributed sweep coverage algorithm of multi-agent systems Includes three applications to demonstrate the advantages of cooperative coverage control approaches
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