Distributed consensus of second‐order multiagent systems with nonconvex input constraints

Summary This paper addresses the input constrained consensus of second‐order multiagent systems with nonconvex constraints. A new update law is proposed to make the position states of all agents converge to a common point and the velocities converge to zero, while the input of each agent stays in a...

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Bibliographic Details
Published inInternational journal of robust and nonlinear control Vol. 28; no. 11; pp. 3657 - 3664
Main Authors Mo, Lipo, Lin, Peng
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 25.07.2018
Subjects
Computer simulation
constrained consensus
Constraints
Convergence
Coordinate transformations
Graph theory
Matrix theory
Multiagent systems
nonconvex constraint
nonlinear protocol
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Summary:Summary This paper addresses the input constrained consensus of second‐order multiagent systems with nonconvex constraints. A new update law is proposed to make the position states of all agents converge to a common point and the velocities converge to zero, while the input of each agent stays in a certain constraint set. The closed‐loop system is first converted to an equivalent system by taking a novel coordinate transformation. Then, it is proved that the input constrained consensus can be achieved if the graphs jointly have directed spanning trees by using the Metzler matrix theory. Finally, simulations are provided to demonstrate the effectiveness of the proposed algorithm.
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.4076