Finite-Time Adaptive Bipartite Consensus Tracking Control for Constrained Nonlinear MASs: A Locally Optimal Bipartition Strategy

This article introduces a finite-time adaptive bipartite consensus tracking control algorithm leveraging an improved nonlinear mapping (NM), capable of implementing the prescribed asymmetric full-state constraint requirements for nonlinear heterogeneous multiagent systems (MASs) under actuator deception attacks. First, a locally optimal bipartition strategy is proposed in this article to enable bipartite consensus tracking control within unbalanced directed graph. Unlike most previous full-state-constrained controls employing the barrier Lyapunov function (BLF), the proposed algorithm is derived from building a state-dependent NM function that can achieve one-to-one mapping for the original function and constructing a new coordinate transformation, leading to the solution of full-state-constrained performance control without the feasibility conditions on the control signals. By means of the proposed practical finite-time stability criterion, the novel design aims at constructing finite-time controllers that can ensure the existence and nonsingularity of the finite-time term in each control signal, which are oblivious in the existing results on finite time control. What’s more, the designed controller even under actuator deception attack achieves that: 1) the bipartite consensus tracking errors converge to a small area containing zero in a finite time; 2) the prescribed asymmetric full-state constraints are obeyed. At last, the availability of the proposed design solution is clarified by virtue of single-link robot systems.