Model Predictive Control of a Three-Wheeled Omnidirectional Mobile Robot Including Static and Dynamic Friction Compensation

The field mobile robots control has been object of study in the last decades. In this field, omnidirectional mobile robots have stood out due to their mobility and maneuverability, being able to move in any direction and perform maneuvers in small spaces. A basic task to control the movement of mobile robots is to follow a given trajectory parameterized at time t. One of the major limitations to achieving good performance lies in the presence of non-linear elements that are difficult to describe analytically. These nonlinear phenomena, such as friction and saturation of the actuators, can negatively affect the performance of the system if they are not properly modeled. This work aims to implement and analyze the performance of a predictive control algorithm applied to a non-linear model of a three-wheel omnidirectional mobile robot within the scope of trajectory tracking. A linearizing feedback action is made to compensate for friction. A linear predictive controller with constraints will be designed to control the linear and angular velocities of the robot. The tuning parameters are directly related to the cost function that is minimized in order to obtain an optimum control sequence. Restrictions on state and control inputs can be considered directly. In this way, control actions that respect the limits of the actuators will be generated automatically.