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无人驾驶拖拉机田间运行轨迹跟踪控制系统设计

Design of Tracking Control System for Unmanned Tractor Field Trajectories
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摘要 现代农业面临劳动力短缺和成本上涨等问题,无人驾驶拖拉机可以减少对人工的依赖,降低劳动成本。然而,由于田间地形复杂多变和环境因素的影响,无人驾驶拖拉机在作业过程中路径规划与跟踪是保证无人驾驶拖拉机正常运行的基础条件与技术支持。该文采用多传感器融合技术,包括GPS、惯性导航系统(INS)、视觉传感器和激光雷达,设计一种无人驾驶拖拉机田间运行轨迹跟踪控制系统,并通过建立拖拉机运动学模型和动力学模型,设计了基于模糊控制和PID控制的复合控制算法,实现拖拉机的轨迹跟踪控制。该系统能够自适应地调整控制参数,克服田间复杂地形和环境变化对运行轨迹的影响。通过田间实地测试验证了系统的有效性和稳定性,结果表明该系统在不同地形条件下均能实现高精度的轨迹跟踪,为无人驾驶农业机械的应用提供了有力的技术支持。 Modern agriculture faces the problems of labor shortage and rising costs,and driverless tractors can reduce the dependence on labor and lower labor costs.However,due to the complexity and variability of field terrain and environmental factors,path planning and tracking of unmanned tractors during operation is the basic condition and technical support to ensure the normal operation of unmanned tractors.In this article,we adopt multi-sensor fusion technology,including GPS,inertial navigation system(INS),vision sensor and LiDAR,to design a trajectory tracking control system for unmanned tractor field operation,and design a composite control algorithm based on fuzzy control and PID control to realize trajectory tracking control of the tractor by establishing the kinematics model and dynamics model of the tractor.The system is able to adaptively adjust the control parameters to overcome the influence of complex terrain and environmental changes on the trajectory in the field.The effectiveness and stability of the system are verified through field tests,and the results show that the system can realize high-precision trajectory tracking under different terrain conditions,which provides strong technical support for the application of driverless agricultural machinery.
作者 卢越 朱省委 吴晓蕊 LU Yue;ZHU Shengwei;WU Xiaorui(Zhengzhou University of Industrial Technology,Zhengzhou 451100,China)
出处 《农机使用与维修》 2024年第9期27-31,共5页 Agricultural Machinery Using & Maintenance
基金 教育部产学合作协同育人项目(230907213253411)。
关键词 无人驾驶拖拉机 轨迹跟踪 控制系统 多传感器融合 模糊控制 PID控制 driverless tractor trajectory tracking control system multi-sensor fusion fuzzy control PID control
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