An Unmanned Vehicle Trajectory Tracking Method based on Improved Model-free Adaptive Control Algorithm

Abstract

In order to solve the dynamic modeling and parameter identification problems of unmanned vehicles trajectory tracking control, a mathematical model of unmanned vehicle trajectory tracking is designed based on the data-driven model-free adaptive control method, which does not depend on the precise dynamic model of the unmanned vehicle. The model-free adaptive control method is extended to the unmanned vehicle trajectory tracking control, and the model-free controller is designed and applied to the driverless vehicle trajectory tracking control. Aiming at the problem that the general compact form dynamic linearization model-free adaptive control (CFDL-MFAC) algorithm cannot converge in vehicle trajectory tracking control, combined with the dynamic characteristics of unmanned vehicles, an improved model-free adaptive control algorithm is proposed in this paper. The simulation results verify the effectiveness and feasibility of the algorithm. Mathematical simulation results show that the improved model-free adaptive algorithm of the designed unmanned vehicle is effective and can effectively implement the trajectory tracking control of the unmanned vehicle. At the same time, the design of the controller does not depend on the kinematics and dynamics models of the unmanned vehicle, and it has high control accuracy.