Smooth Reference Tracking of a Mobile Robot using Nonlinear Model Predictive Control

In this paper, path following control and trajectory tracking control of a mobile robot have been studied. Reference convergence in a path following problem and time convergence in a trajectory tracking problem are considered in the cost function of the nonlinear model predictive control framework. The benefit of path following control is that the path following controller eliminates aggressiveness of the tracking controller by forcing convergence to the desired path in a smooth way. Thus, we incorporate this benefit to the trajectory tracking problem to achieve smooth convergence to the reference and to achieve time convergence of trajectory tracking. Furthermore, by using nonlinear model predictive control, input constraints can be handled straightforwardly in the optimization problem so that the robot can travel safely. Our controller was validated by simulation and real-world experiments with a unicycle-type mobile robot were also conducted.