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通过交互力-基于阻抗方法和极端寻求优化来对机器人操纵器进行协作控制
1School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621010, China.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
这项研究介绍了使用极端寻找的机器人操纵器的自适应阻抗控制. 它通过实时优化参数来简化接触阻抗调整,提高机器人控制性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 机械电子学是什么意思 机械电子学
背景情况:
- 机器人操纵器需要精确控制涉及物理互动的任务.
- 传统的阻抗控制方法通常依赖于扭矩传感器,并与不确定性作斗争.
- 需要适应性控制策略来提高在动态环境中的稳定性和性能.
研究的目的:
- 为机器人操纵器引入一种新的自适应阻抗控制策略.
- 通过使用干扰观察员来消除对扭矩传感器的需求.
- 为了实现实时,在线优化各种任务的控制参数.
主要方法:
- 利用极端寻找技术进行自适应参数优化.
- 实施基于模型的干扰观察器 (DOB) 来估计接触力.
- 开发了一个阻抗向量来弥补电机的不确定性和未知的合.
- 整合了联合跟踪错误和接触力波动到成本函数中.
主要成果:
- 拟议的控制器在没有扭矩传感器的情况下成功估计了接触力.
- 通过极端搜索实时实现了控制参数的自适应优化.
- 控制器展示了一个精简的设计来调整操纵器接触阻抗.
- 实验结果验证了基于成本函数变化的在线调整能力.
结论:
- 适应性阻抗控制策略为机器人操纵提供了更有效和更强大的方法.
- 极端寻找提供了一种有效的机制,用于在线调整控制参数.
- 该方法提高了操作器在需要精确接触力控制的任务中的性能.
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