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无人驾驶农机装备的模糊PI-LQR转向控制算法

姬江涛 王启洲 张玉成 韩志豪

河南科技大学学报(自然科学版)2024,Vol.45Issue(3):9-16,8.
河南科技大学学报(自然科学版)2024,Vol.45Issue(3):9-16,8.DOI:10.15926/j.cnki.issn1672-6871.2024.03.002

无人驾驶农机装备的模糊PI-LQR转向控制算法

Fuzzy PI-LQR Steering Control Algorithm for Unmanned Agricultural Equipment

姬江涛 1王启洲 1张玉成 2韩志豪1

作者信息

  • 1. 河南科技大学 农业装备工程学院,河南 洛阳 471003
  • 2. 中国科学院 智能农业机械装备工程实验室,北京 100086
  • 折叠

摘要

Abstract

The steering system of unmanned agricultural machinery exhibits the problems of nonlinearity and time delay when operating at low flow and small angle control.This phenomenon can lead to steering control overshoot or delay,resulting in the inability to accurately track the path preview point quickly.To address this issue,an inner-outer loop control algorithm based on fuzzy proportional-integral-linear quadratic regulator(PI-LQR)data fusion was proposed.The algorithm employs fuzzy PI control as the inner loop,adapting PI parameters through fuzzy logic operations based on steering angle error and its rate of change for closed-loop control of steering angle.The algorithm utilizes LQR control as the outer loop,incorporating the steering angle error from the inner loop based on agricultural machinery XY lateral angle control to further enhance the precise control of steering for unmanned agricultural machinery.Joint simulations using Carsim and Matlab/Simulink demonstrate that for a 100 m double lane change path,the maximum lateral error is less than 0.18 m,and the maximum yaw error is less than 0.067 rad.Real vehicle tests indicate that the maximum lateral error is less than 0.26 m for a 100 m double lane change path.Compared with the PID pure tracking control algorithm,the maximum lateral error is reduced by 0.19 m.

关键词

无人驾驶/转向系统/模糊PI/LQR/内外环控制

Key words

autonomous driving/steering system/fuzzy PI/LQR/inner and outer loop control

分类

农业科技

引用本文复制引用

姬江涛,王启洲,张玉成,韩志豪..无人驾驶农机装备的模糊PI-LQR转向控制算法[J].河南科技大学学报(自然科学版),2024,45(3):9-16,8.

基金项目

国家重点研发计划项目(2023YFD2001100) (2023YFD2001100)

河南省重大科技专项项目(221100110800,231100220200) (221100110800,231100220200)

河南科技大学学报(自然科学版)

OA北大核心CSTPCD

1672-6871

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