Event-Triggered Tracking Control for Wheeled Mobile Robot

Abstract

Event-triggered control has achieved good results in reducing redundant transmission of network resources in wheeled mobile robots (WMR). Although event-based velocity control methods have made some progress in solving the WMR trajectory tracking problem, these methods rely on the assumption that the kinetic moment controller can accurately provide the required velocity of the motion model and ignore the nonlinear characteristics such as wheel slip and universal wheel friction that exist in complex environments. This makes it difficult to achieve accurate tracking in practical applications. For this reason, an event-triggered sliding mode tracking control strategy is proposed to address the problems of uncertainty in the WMR center of mass position, perturbation of universal wheel friction, and wheel slip. Specifically, the corresponding event-triggered mechanisms are designed for the velocity and current loops, and combined with the designed virtual velocity control law and dynamic torque control law, to ensure that the error system is asymptotically stabilized while reducing the waste of resources. The neural network is also used to estimate the unknown friction force, which eliminates the influence of the perturbation brought by the universal wheel. Simulation results show that the control scheme has the ability to handle trajectory tracking and save transmission resources.