Path tracking with speed adjusting for car-like robots based on a multilayer MPC framework

Car-like robot is a front wheel steering robot with a structure similar to that of an unmanned vehicle, which is widely used in manufacturing, warehousing, and other industries because of advantages such as simple structure and strong load-bearing capacity. The path tracking control of car-like robots has the characteristics of a smaller system constraint range and lower degree of component standardisation and is now getting more and more widespread attention. At present, there are many research works dedicated to the path tracking control of car-like robots, but these research works have not yet considered the correlation between active speed adjusting and path tracking, and the existing control system can only set the longitudinal speed to a low value to ensure a high path tracking control accuracy. Meanwhile, among active speed control strategies for other mobile equipment, multilayer model predictive control (MMPC) based on model predictive control (MPC) has the advantage of strong compatibility with the error source, but the existing MMPC system adopts linear MPC (LMPC) as the lower path tracking control algorithm. Typical LMPC design methods are unable to take into account the reference path information in front of a car-like robot and are not accurate enough at higher longitudinal speeds, so the longitudinal speeds of existing MMPC systems are still low. To address these problems, an MMPC-based active speed adjusting path tracking control framework is introduced, combining the feedforward MPC (FMPC) path tracking control algorithm with the nonlinear MPC (NMPC) speed adjusting algorithm, and constructing a new MMPC-based path tracking control system for car-like robots with active speed adjusting. The proposed MMPC system is tested by joint simulation with MATLAB and CarSim. In the simulation results, the proposed MMPC system can achieve higher accuracy path tracking at higher average travelling speeds, with the maximum magnitude of displacement error of 0.1838 m and heading error of 0.1350 rad at an average travelling speed of 4.2859 m-s-1. At higher longitudinal speeds, the proposed MMPC achieves higher accuracy compared to the constant speed FMPC, NMPC systems and the existing MMPC system. Under the same working conditions, the error of the FMPC system is dispersed, and the proposed MMPC system can reduce the maximum displacement error by 46.29% and 62.22% compared with the existing NMPC and MMPC systems. When higher accuracy can be guaranteed, the average travelling speed of the proposed MMPC system is higher, and it can increase the average travelling speed by 43.06% and 317.48% compared with existing FMPC and MMPC systems with smaller errors, which is close to the index of the NMPC system.