Sampled-data distributed protocol for coordinated aggregation of multi-agent systems subject to communication delays |
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Affiliation: | 1. School of Mathematics, Southeast University, Nanjing 210096, China;2. School of Automation and Electrical Engineering, Linyi University, Shandong, Linyi 276005, China;3. College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China;4. Texas A&M University at Qatar, Doha 23874, Qatar;5. Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia;1. Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada;2. Concordia Institute for Information System Engineering (CIISE), Concordia University, Montreal, QC, Canada;1. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China;2. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;3. School of Mathematics and Statistics, Shandong University of Technology, Zibo, China |
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Abstract: | This paper studies the coordinated aggregation problem of a multi-agent system. Particularly, all the agents reach a consensus within a pre-specified target region. However, only a subset of agents have access to this target region, and each agent merely interacts with its neighbors by communication. Moreover, there exist unknown heterogeneous delays in communication channels. The underlying communication topology is characterized by a digraph. To accommodate the practical digital disposal, a sampled-data distributed protocol is proposed, where the sampling is asynchronous in the sense that the sampling periods of distinct agents are heterogeneous. The resulting closed-loop system from the proposed sampled-data distributed protocol is in a hybrid fashion that the continuous system is fed-back by using discrete states at sampling instants. The convergence performance of this hybrid closed-loop system is analyzed based on the contraction theory. More specifically, it is first shown that all the states are coordinated to aggregate within the target region, i.e., coordinated aggregation. With this result, it is next shown that all the states are coordinated towards a consensus, i.e., state agreement. These together guarantee the fulfillment of the concerned coordinated aggregation objective. Finally, a simulation example is given to validate the theoretical results. |
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Keywords: | Multi-agent system Coordinated aggregation Consensus Sampled-data protocol Distributed protocol Asynchronous sampling Communication delay |
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