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Adaptive Prescribed Finite-Time Bipartite Consensus Control for Nonaffine Nonlinear MASs Under Structurally Unbalanced Topology

Xiaomei Wang, Yongduan Song, Xudong Zhao, Huanqing Wang, Ding Wang, Ben Niu

Year
2025
Citations
5

Abstract

This article investigates an adaptive bipartite consensus tracking control algorithm for a class of heterogeneous nonaffine nonlinear multiagent systems (MASs) with prescribed finite-time tracking performance under an unbalanced communication topology. In the case of an unbalanced digraph, a novel locally optimal bipartition strategy is proposed to transform the unbalanced communication topology into a structurally balanced one, thereby enabling the implementation of bipartite consensus tracking control. To achieve the expected tracking performance, the design philosophy focuses on developing a prescribed finite-time performance function (PFTPF), capable of preassigning the convergence time and accuracy precisely beforehand. The explored adaptive control algorithm can ensure that the whole signals concerning the closed-loop MASs remain bounded while the bipartite consensus errors converge to a predetermined range around zero within the prescribed finite time. Ultimately, the simulation results on robotic systems prove the availability of the developed design solution.

Keywords

Bipartite graphNonlinear systemTopology (electrical circuits)Control theory (sociology)MathematicsControl (management)Computer sciencePhysicsDiscrete mathematicsArtificial intelligence

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