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

This article focuses on the consensus and tracking problem of nonlinear multiagent 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.