无人农业机械的自适应路径跟踪控制,具有基于RLS-ELM的固定时间超扭转滑动模式
Zhijian Chen1, Jianjun Yin1, Sheikh Muhammad Farhan2
1School of Agricultural Engineering, Jiangsu University, Zhenjiang, China.
Frontiers in plant science
|October 6, 2025
概括
这项研究引入了一种用于无人农用车辆的新型自适应路径跟踪控制,提高了精度和稳定性. 新方法显著减少了跟踪错误,改善了机器的自主操作.
科学领域:
- 机器人和自动化机器人与自动化
- 控制系统工程 控制系统工程
- 农业工程 农业工程
背景情况:
- 无人农业机械的智能操作依赖于准确的路径跟踪.
- 传统方法与振荡和外部干扰作斗争,限制了性能.
研究的目的:
- 为无人农业车辆提出固定时间超扭转滑动模式自适应路径跟踪控制.
- 提高农业机器路径跟踪的稳定性和适应性.
主要方法:
- 利用调节最小平方极端学习机器 (RLS-ELM) 来提高适应性.
- 设计了一个通用的终端滑动模式表面,包含横向和方向偏差.
- 与RLS-ELM一起开发了一个超扭曲滑动模式控制规律,用于对干扰进行补偿.
主要成果:
- 拟议的极端学习机器-自适应固定时间通用超扭曲 (ELM-AFGST) 方法将横向平均绝对误差降低了24.5%和27.4%.
- 与现有方法相比,标题平均绝对误差减少了5.4%和30.8%.
- 实地实验验证了ELM-AFGST方法的优越性能.
结论:
- 开发的路径跟踪控制为无人驾驶农用车提供了强大的解决方案.
- 该方法为农业中高精度路径跟踪提供了坚实的理论框架.
- 这一进步支持自主农业机械的智能操作和效率.
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