基于安全距离的无人农机路径跟踪抗扰预测控制  

Anti-disturbance predictive control for path tracking of unmanned agricultural vehicles based on safety distance

作　　者：黄臻臻 孙金林[1] 丁世宏[1] HUANG Zhenzhen;SUN Jinlin;DING Shihong(School of Electrical and Information Engineering,Jiangsu University,Zhenjiang 212013,China)

机构地区：[1]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《智能科学与技术学报》2025年第1期86-97,共12页Chinese Journal of Intelligent Science and Technology

基　　金：国家自然科学基金项目(No.62203189,No.62373170);江苏省自然科学基金项目(No.BK20220518);中国博士后科学基金项目(No.2024M751187);江苏大学高级人才基金项目(No.22JDG044)。

摘　　要：为提升无人农机在多障碍复杂作业场景下的路径跟踪性能,提出了一种基于安全距离的抗扰预测控制方案。该方案利用预测控制的自主学习能力,通过与作业场景的交互,实现了无人农机在复杂作业场景下的高效避障。首先,设计扩张状态观测器以精确估计农机系统中的未知扰动,并将其纳入非线性预测模型中,从而提升路径跟踪控制系统中状态预测的精度以及抗干扰性能。其次,设计无人农机参考点自动寻优算法,避免无人机在路径跟踪过程中过度转向。基于对数函数缩放构造新颖的避障惩罚项,确保在无人农机路径跟踪过程中与多重障碍始终保持预设的安全距离。最后,在成本函数中融入横向偏差与航向偏差信息,并结合避障惩罚项,通过在线求解非线性受限优化问题设计抗扰模型预测控制方案。仿真结果表明,该控制方案具有较高的路径跟踪精度,并能适应不同的安全距离和障碍物位置,实现有效避障。To enhance the path tracking performance of unmanned agricultural vehicles in complex working scenarios with multiple obstacles,this paper proposes an anti-disturbance predictive control scheme based on safe distance.This control scheme leverages the autonomous learning capabilities of predictive control to achieve efficient obstacle avoidance maneuvers for unmanned agricultural vehicles in complex operational scenarios through interaction with the working environment.Initially,an extended state observer is designed to accurately estimate the unknown disturbance within the agricultural vehicle system and incorporate it into the nonlinear predictive model,thereby improving the precision of state prediction and disturbance rejection in the path tracking control system.Subsequently,an automatic optimization algorithm for the reference point of the agricultural vehicle is designed to prevent excessive steering during path tracking.Then,a novel obstacle avoidance penalty term is constructed based on logarithmic function scaling to ensure that the agricultural vehicle maintains a preset safe distance from multiple obstacles during path tracking.Building on this,the cost function is integrated with lateral offset and heading offset information,combined with the obstacle avoidance penalty function,and an anti-disturbance model predictive control scheme is constructed by solving the nonlinear constrained optimization problem online.Simulation results demonstrate that the control scheme proposed in this paper has superior path tracking accuracy and can effectively avoid obstacles while adapting to different safe distance settings and obstacle positions.

关 键 词：无人农机 路径跟踪控制 模型预测控制 安全避障 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]