Anti-sideslip has not been paid much attention by most researchers of wheeled mobile robots. And some existing anti-sideslip path tracking control methods based on switching control have problems such as relying on design experience. To enable the wheeled mobile robot to prevent sideslip and track the reference path at the same time, we propose an anti-sideslip path tracking control method based on a time-varying local model. The principle of this method is to make model predictions and rolling optimizations in the robot coordinate system in each control period. The proposed controller is tested by MATLAB simulation. According to the simulation results, the proposed controller can prevent sideslip when the wheeled mobile robot tracks the reference path. Even if the ground adhesion coefficient is low, the maximum lateral speed of the robot is only 0.2159 m/s. While preventing sideslip, the proposed controller is able to keep the displacement error of path tracking within 0.1681 m. Under the same conditions, the maximum absolute value of the displacement error of the proposed controller is at least 55.15% smaller than that of the controller based on the global model.

Since the curvature of urban roads varies greatly, path tracking in this scenario faces the problem that it is difficult to simultaneously guarantee high accuracy and high efficiency. According to previous work on path tracking, nonlinear model predictive control (NMPC) has good accuracy when the curvature of the reference path varies. But when it is hoped to further improve the efficiency, the accuracy of NMPC-based path tracking control is still difficult to guarantee. So, we combined fuzzy control and NMPC to design a path tracking controller, which can adjust the speed to ensure high accuracy and high efficiency. Then, we verified the proposed controller through the joint simulation of MATLAB/Simulink and CarSim. When the simulation environment is consistent, the maximum absolute values of the displacement error and the heading error of the proposed controller are 80.4 % and 46.6 % smaller than those of the NMPC controller. The proposed controller is robust to positioning error, and it can operate normally when the positioning error is not greater than 0.04 m. Besides, the real-time performance of the proposed controller can be ensured by reducing the control horizon. The maximum calculation time in the simulation only accounts for 28 % of the control period.