Prescribed-Time Tracking Control for Uncertain Nonlinear Multiagent Systems With Matched and Mismatched Disturbances

This article addresses the tracking control issue within a prescribed-time (PT) for nonlinear multiagent systems (MASs) affected by model uncertainties and external disturbances. First, the approximation characteristics of fuzzy logic systems are employed to design corresponding adaptive fuzzy control laws, which approximate the unknown parts of the system to approximate known values. Then, by utilizing the fuzzy inputs from multiple agents and defined rules, the system adapts to external mismatched disturbances. Next, a novel time-scale function is designed as part of the controller gain. Unlike traditional gain functions, this function ensures the system achieves consensus within a predetermined time while avoiding infinite growth, thereby ensuring the boundedness of the control signals. Introducing this function into the controller, along with the adaptive fuzzy control laws and intermediate control laws, constructs an adaptive control law to achieve control over each agent and achieve PT consensus of the uncertain system. In the controller design, the complexity of proving system stability is reduced by avoiding fractional-order Lyapunov differential inequalities, and each agent has corresponding control parameters. Finally, the efficacy of the results from the theoretical analysis is confirmed by a pair of simulation examples.