This paper investigates the prescribed-time tracking control problem for a cluster system of unmanned ground vehicles (UGVs), aiming to address the challenges posed by nonlinear multi-agent systems under multiplicative measurement noise. A nonlinear disturbance observer, designed within the RISE (Robust Integral of the Sign of the Error) framework, is implemented to ensure robustness to uncertain system dynamics and to effectively compensate for time-varying disturbances. By designing a novel time-varying gain control strategy and leveraging a Lyapunov-based control framework, a feedback control law is proposed to ensure that the tracking error and velocity error converge to zero within a prescribed time. The proposed method ensures mean-square stability of the closed-loop system under multiplicative noise, which is typical in wireless and sensor-based applications. Simulations verify the robustness and accuracy of the proposed method, showing convergence within 0.2 seconds and a position error limited to 0.5 units even under large initial errors and strong noise interference. The proposed approach provides a reliable and efficient control strategy for UGV swarms operating in uncertain and noisy environments.
Pang et al. (Mon,) studied this question.