Fixed-Time Distributed Average Tracking for a Class of Nonlinear Multiagent Systems With Unity Relative Degree
针对受外部干扰的非线性多智能体系统，提出一种分布式控制框架，使所有智能体的输出在固定时间内收敛到多个非线性参考信号的平均轨迹，并通过数值仿真验证了有效性。
This article investigates the fixed-time distributed average tracking (DAT) problem for nonlinear multiagent systems with unity relative degree under external disturbances. A distributed control framework is developed to guarantee fixed-time convergence of all agents' outputs to the target trajectory, which is defined as the average of multiple nonlinear reference signals. The approach consists of three main components. First, a steady-state generator is introduced to reconstruct the desired trajectory. Using this generator, a distributed observer is designed to estimate the target trajectory while ensuring robustness against initialization errors. Subsequently, an observer-based output-feedback controller is developed to guarantee the convergence of each agent's output to its corresponding reference signal within a fixed time. Through rigorous theoretical analysis, it is proved that the proposed control architecture ensures fixed-time convergence to the target trajectory, effectively solving the fixed-time DAT problem. The effectiveness of the proposed method is validated through numerical simulations.