Event-Based Model Predictive Tracking Control of Nonholonomic Systems With Coupled Input Constraint and Bounded Disturbances

This paper studies the event-based model predictive control (EMPC) for tracking of nonholonomic mobile robot with coupled input constraint and bounded disturbances. First, an event-triggering mechanism is presented by designing a threshold for the error between the actual trajectory and the predicted one, aiming at reducing the computational load. Second, a model predictive control strategy is developed based on the event-triggering mechanism. Recursive feasibility is guaranteed by designing a robust terminal region and the proper parameters. We show that the tracking system is practically stable and also provides a convergence region for the tracking error. The convergence region indicates that the tracking performance is negatively related to the minimal interevent time as well as the bound of the disturbances. Finally, simulation results show that the computation load is significantly reduced and illustrate the efficiency of our proposed strategy.

I. Introduction

Tracking control of nonholonomic robots is a fundamental problem in cooperative control [1], formation control [2]– [4], and path planning [5]. In practice, the nonholonomic robot is constrained by its mechanical dynamics to move along its orientation [6], [7], which may lead to the system controllability lost when its states converge to zero [8], [9]. So far, many approaches have been developed for the control of nonholonomic robots, e.g., dynamic feedback linearization [10], backstepping technique [7], periodic feedback technique [11], etc. However, these techniques ignore the mechanical constraint such as input saturation.