Predefined-Time Distributed Average Tracking of Multiple Time-Varying Reference Signals With Bounded and Lipschitz-Type Derivatives
Xiongjie Lin, Yanzhi Wu, Qingpeng Liang, Yue Wu, Pu Li, Ruwei Feng, Hongsheng Zhou, Liang Feng · IFAC-PapersOnLine · 2025
The paper addresses the problem of distributed average tracking (DAT) for nonlinear reference signals in multi-agent systems. Based on predefined-time stability theory, two novel control algorithms are proposed: one for reference signals with bounded derivatives, and the other for nonlinear signals whose derivatives satisfy the Lipschitz condition. First, a distributed estimator is designed to estimate the average of multiple time-varying reference signals. Then, a tracking controller is designed to enable the multi-agent system to precisely track the average of the reference signals within a specified time, with only local interactions required. Compared to existing methods, the proposed algorithms simplify the complexity of parameter design and enhance their engineering applicability. Finally, the convergence of the algorithms within the predefined time is rigorously proven through theoretical analysis, and numerical simulations are used to verify their effectiveness.