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Multiagent Containment Control With Nonconvex States Constraints, Nonuniform Time Delays, and Switching Directed Networks
This brief studies the constrained containment control problem of continuous-time multiagent systems with nonconvex states constraints, nonuniform time delays, and switching directed networks. A distributed containment control algorithm consisting of nonlinear projection, nonlinear constraints, and...
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| Published in: | IEEE transaction on neural networks and learning systems 2020-11, Vol.31 (11), p.5021-5028 |
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| Main Authors: | , , |
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| cited_by | cdi_FETCH-LOGICAL-c351t-bb0c6b34f25354b72abdcfcc7ebdabddccc7787e96925a298171bc1cc0220ec43 |
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| cites | cdi_FETCH-LOGICAL-c351t-bb0c6b34f25354b72abdcfcc7ebdabddccc7787e96925a298171bc1cc0220ec43 |
| container_end_page | 5028 |
| container_issue | 11 |
| container_start_page | 5021 |
| container_title | IEEE transaction on neural networks and learning systems |
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| creator | Huang, Yi Duan, Mengmeng Mo, Lipo |
| description | This brief studies the constrained containment control problem of continuous-time multiagent systems with nonconvex states constraints, nonuniform time delays, and switching directed networks. A distributed containment control algorithm consisting of nonlinear projection, nonlinear constraints, and communication delays is proposed. Based on the model transformation technique, convex analysis method, and the Lyapunov function, we prove that all agents finally converge into the convex hull formed by the given stationary points with arbitrarily bounded communication delays and arbitrarily switching networks as long as each agent jointly has at least one path from the given points to itself. Finally, a numerical example is included to show the effectiveness of theoretical results. |
| doi_str_mv | 10.1109/TNNLS.2019.2955678 |
| format | article |
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A distributed containment control algorithm consisting of nonlinear projection, nonlinear constraints, and communication delays is proposed. Based on the model transformation technique, convex analysis method, and the Lyapunov function, we prove that all agents finally converge into the convex hull formed by the given stationary points with arbitrarily bounded communication delays and arbitrarily switching networks as long as each agent jointly has at least one path from the given points to itself. Finally, a numerical example is included to show the effectiveness of theoretical results.</description><identifier>ISSN: 2162-237X</identifier><identifier>EISSN: 2162-2388</identifier><identifier>DOI: 10.1109/TNNLS.2019.2955678</identifier><identifier>PMID: 31870998</identifier><identifier>CODEN: ITNNAL</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Computational geometry ; Constraints ; Containment ; Containment control ; Control algorithms ; Control theory ; Convexity ; Delay effects ; Delays ; Learning systems ; Liapunov functions ; Multi-agent systems ; Multiagent systems ; Network topology ; Networks ; nonconvex states constraints ; Nonlinear control ; nonuniform time delays ; Switches ; Switching ; switching directed networks ; Timing</subject><ispartof>IEEE transaction on neural networks and learning systems, 2020-11, Vol.31 (11), p.5021-5028</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Xplore (Online service) |
| subjects | Algorithms Computational geometry Constraints Containment Containment control Control algorithms Control theory Convexity Delay effects Delays Learning systems Liapunov functions Multi-agent systems Multiagent systems Network topology Networks nonconvex states constraints Nonlinear control nonuniform time delays Switches Switching switching directed networks Timing |
| title | Multiagent Containment Control With Nonconvex States Constraints, Nonuniform Time Delays, and Switching Directed Networks |
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