Robust Bipartite Tracking Control for Multi-agent Systems with Co-competition Interactions via the NN-UDE Approach

This paper focuses on the bipartite consensus tracking problem of multi-agent systems with co-competition interactions. The dynamics of the leader agent is uncertain for each follower agent and there exist unknown disturbances in the control input channel of followers. To solve this problem, a robust bipartite consensus tracking control scheme is proposed by adopting the NN-UDE approach. NN-UDE is the approximation/estimation structure that includes two components. One component is the neural networks (NNs), which can be used to approximate the uncertainties of leader agent; the other component is the uncertainty and disturbance estimator (UDE), which can estimate the unknown disturbances of follower agents. The effective coupling of NN and UDE can improve the robustness of the system and solve the bipartite consensus tracking control problem. Finally, the simulation results are given to verify the effectiveness of the proposed control scheme.