LAUSR

This paper presents a novel robust consensus control method for multiple nonholonomic wheeled mobile robots (MNWMRs). The method involves developing a dynamic sliding mode tracker based on the Average Dwell Time (ADT) technique, which tracks the velocity state onto the kinematic auxiliary vector through torque control. While the communication topologies are randomly switched to achieve consensus control of virtual trajectories by the controlled robots. Furthermore, considering the influence of strong external disturbances and nonlinear dynamic uncertainties in the system, two control methods, Uncertainty and Disturbance Estimator (UDE) and Radial Basis Function Neural Network (RBF NN), are combined. The former is used to ensure the robustness of the closed‐loop system, and the latter improves its adaptability accordingly. Moreover, a new filter is developed for sinusoidal external disturbances with measurable angular frequency, leading to the asymptotic convergence of disturbance error towards the origin. Then, the stability analysis of the corresponding closed‐loop control systems is then performed by the use of Lyapunov analysis. Finally, the simulation examples are provided to verify the effectiveness of the designed control strategy.