Concurrent Learning-Based Adaptive Trajectory Tracking Control of Omnidirectional Mobile Robot

This paper investigates the trajectory tracking control problem of omnidirectional mobile robot (OMR) with unknown parameters. A novel concurrent learning-based adaptive tracking control strategy is proposed. Different from currently available adaptive control schemes, the parameter estimation error in this paper can exponentially converge to zero under a mild rank condition, by resorting to concurrent learning technique. This implies that the identification of unknown parameters is achieved. Moreover, the trajectory tracking error can also tend to zero exponentially. Unlike some results with asymptotical convergence rate, the convergence rate of the tracking error can be improved in this paper. Finally, simulation results are provided to validate the effectiveness of the proposed control scheme.