Designing Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot Using Lager functions and Exponential Data Weighting

Numerous studies have been devoted to motion control of wheeled mobile robots in recent years. Among them, trajectory tracking has received much attention.. A feed-forward and feedback control structure for trajectory tracking is used to circumvent the limitation of Brockett’s theorem. Feed-forward control is calculated according to the reference trajectory, it can not compensate instrumentation and initial state errors, therefore a feedback controller is utilized as well. In this paper a model predictive controller is used as the feedback controller. Since the initial state is not often matched to the desired trajectory, rapid tracking of the trajectory in early steps is very important. In this paper a model predictive controller with laguerre functions and another one with exponential data weighting is used to reduce tracking error in early steps. According to simulation results, reference trajectory tracking is improved through laguerre functions in model predictive controller.