Adaptive Finite Time Output Feedback Bipartite Tracking Control for Nonlinear Multiagent Systems

This paper investigates event-triggered based finite-time bipartite consensus tracking control problem for multi-agent systems (MASs) over signed directed graphs. Compared with the existing related results, the main features of the results presented in this paper are as follows: (
i
) The strict limitation for nonlinear MASs with a structurally balanced digraph is removed by introducing a prioritized strategy. (
ii
) A state estimator is constructed by combining neural networks (NNs), which reconstructs the immeasurable system states of each agent in nonstrict-feedback form for the first time and approximates the completely unknown nonlinearities that exist in the system. (
iii
) A new distributed control algorithm, named finite-time distributed control strategy is designed by introducing a novel first-order filter, which ensures that the consensus errors can obtain a fast convergence. (
iv
) The results are successfully extended to the event-based bipartite tracking control for MASs by using relative threshold strategy. Moreover, the proposed control algorithm is applied to the consensus problem of a group of forced damped pendulums (FDPs). Based on backstepping method and Lyapunov stability theory, the distributed consensus tracking errors can converge to a small neighborhood of the origin at a finite-time under the proposed protocol, and all the signals of the closed-loop system remain bounded. Finally, the simulation results illustrate the validity of the proposed schemes.
Note to Practitioners
—The studies of the bipartite consensus problems of multi-agent systems (MASs) have gained great attention due to its applications in multi-spacecraft systems, natural networks, and biological communities, and a new event-triggered based finite time bipartite tracking consensus control method for multi-agent systems (MASs) is studied in this paper. In practical applications, the finite time method can obtain the optimal control performance in time. Then, in order to save the communication and computation resources for the nonlinear MASs, this paper extends the proposed control strategy to the event-based bipartite tracking control problem for MASs by using the relative threshold event-triggered rules, which greatly conserves the communication resources between the control signal and the actuator. In addition, the dynamic model and backstepping technology used in this paper are general and practical.