动态参数识别和自适应控制,用于机器人环境交互的轨迹缩放
PloS one
|July 13, 2023
概括
这项研究引入了一个新的机器人控制方案,以改善环境交互. 该方法通过动态参数识别和自适应估计来增强机器人的力量/位置控制.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 机械工程 机械工程
背景情况:
- 与环境接触的机器人需要精确的力量和位置控制.
- 现有的控制方法可能会与动态不确定性和环境相互作用作斗争.
研究的目的:
- 开发一种先进的控制方案,以提高机器人与环境接触时的力量/位置控制性能.
- 集成动态参数识别,轨迹缩放和自适应计算扭矩控制.
主要方法:
- 利用牛顿-欧勒法推导出机器人的动态方程和回归矩阵,减少模型顺序.
- 采用最小平方法用于初始动态参数的识别.
- 实现了适应性参数估计,用于扭矩计算和轨迹缩放,用于接触力管理.
主要成果:
- 拟议的控制方案有效地整合了动态参数识别和自适应控制.
- 模拟证明了组合方法在提高机器人控制性能方面的有效性.
- 轨迹缩放在管理接触力方面被证明是有效的.
结论:
- 拟议的控制方案在环境相互作用期间显著改善了机器人力量/位置控制.
- 动态参数识别,自适应估计和轨迹缩放之间的协同作用对于提高性能至关重要.
- 这种方法为涉及物理接触的复杂机器人任务提供了强大的解决方案.
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