Path Tracking Control of Mobile Robot Based on Preview-Linear Model Predictive Control

Mobile robot, as typical unmanned driving models, are developing rapidly. However, wheeled robots face the risks of side - slipping and path deviation when traveling at high speeds and turning, so path tracking control needs to be optimized. This paper proposes a preview-LMPC path tracking controller. First, an LMPC controller is designed based on the vehicle kinematic model. The prediction model of the LMPC controller is linearized by Jacobian and discretized, the objective function is set, and the control input is obtained by solving a quadratic programming problem. Then, the arc length between the original tracking target point of the LMPC controller and a point on the reference path in front of it is used as the preview distance to determine the preview point. The position and attitude information of the preview point is substituted into the LMPC controller as the position and attitude information of the tracking target point to form the preview-LMPC path tracking controller. Simulations are carried out using MATLAB/Simulink and Carsim software. Under the working conditions of a curve curvature of 0.0133m<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> and a vehicle speed of 8m/s, the best effect is achieved when the preview distance is 0.85m. Compared with the LMPC controller, the maximum absolute value of the displacement error is reduced by 0.2203m, with a reduction amplitude of 88.37%, and no side - slipping occurs. The research shows that the introduction of preview control can improve the accuracy of the LMPC controller. Mobile robot based on preview-linear MPC can effectively improve the tracking accuracy of paths with large curvatures and prevent side - slipping to a certain extent.