Fuzzy backstepping controller for agricultural tractor-trailer vehicles path tracking control with experimental validation

作者：Anzhe Wang, Yefei Wang, Xin Ji, Kun Wang, Meiling Qian, Xinhua Wei, Qi Song, Wen‐Ming Chen, Shaocen Zhang · 发表于：Frontiers in Plant Science · 年份：2024 · DOI：10.3389/fpls.2024.1513544 · 被引用次数：8 · 研究领域：Soil Mechanics and Vehicle Dynamics、Agricultural Engineering and Mechanization、Control and Dynamics of Mobile Robots

Unmanned driving technology for agricultural vehicles is pivotal in advancing modern agriculture towards precision, intelligence, and sustainability. Among agricultural machinery, autonomous driving technology for agricultural tractor-trailer vehicles (ATTVs) has garnered significant attention in recent years. ATTVs comprise large implements connected to tractors through hitch points and are extensively utilized in agricultural production. The primary objective of current research focus on autonomous driving technology for tractor-trailers is to enable the tractor to follow a reference path while adhering to constraints imposed by the trailer, which may not always align with agronomic requirements. To address the challenge of path tracking for ATTVs, this paper proposes a fuzzy back-stepping path tracking controller based on the kinematic model of ATTVs. Initially, the path tracking kinematic error model was established with the trailer as the positioning center in the Frenet coordinate system using the velocity decomposition method. Then, the path tracking controller was designed using the back-stepping algorithm to calculate the target front wheel steering angle of the tractor. The gain coefficient was adaptively adjusted through a fuzzy algorithm. Co-simulation and experiments were conducted using MATLAB/Simulink/CarSim and a physical platform, respectively. Simulation results indicated that the proposed controller reduced the trailer's online time by 36.33%. When followin...