Data-Driven Distributed Predictive Tracking Control for Heterogeneous Nonlinear Multi-Agent Systems With Communication Delays

This paper focuses on the consensus and tracking problem of nonlinear multi-agent systems under communication delays, and proposes a distributed predictive control scheme which is independent of the system model and able to actively compensate for communication delays. First, a consensus-related auxiliary variable and its corresponding estimator are innovatively designed to provide a globally consistent value. Then, the idea of dynamic linearization is adopted to obtain the equivalent linear dynamics of nonlinear agents. Furthermore, a distributed predictive controller is designed with the help of the auxiliary variables and the acquired time-varying linear system model. Compared with the existing schemes, the proposed controller compensates for the delayed signals in an active way, makes the traditional model-based predictive control method get rid of the dependence on the accurate system model, and carries out the rolling prediction in a distributed form. A stability analysis of the closed-loop system is given to illustrate the generality of the designed method. Finally, a numerical simulation verifies the effectiveness of the proposed method.