基于未知的系统动态估计器的道控制,用于液压驱动的下肢外骨架机器人机器人
Jinsong Zhao1, Huidong Hou2, Yunpeng Zhang2
1School of Mechanical Engineering, Yanshan University, Qinhuangdao, 066004, China; Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control, Yanshan University, Qinhuangdao, 066004, China; Key Laboratory of Advanced Forging & Stamping Technology and Science (Yanshan University), Ministry of Education of China, Qinhuangdao, 066004, China; State Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao, 066004, China.
这项研究引入了一种新的漏斗控制 (FC) 策略,使用未知的系统动态估计器 (USDE) 来改进液压驱动下肢外骨架机器人 (HDLLER) 的轨迹跟踪. 该方法有效地弥补不确定性和干扰,提高机器人的性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 生物力学 生物力学
背景情况:
- 液压驱动的下肢外骨架机器人 (HDLLER) 增强了人类的移动性,但在精确控制方面面临着挑战.
- 人机合和系统不确定性阻碍了准确的轨迹跟踪.
研究的目的:
- 为HDDLLERs制定一个强大的控制策略,以解决未知的动态和外部干扰.
- 为了提高下肢外骨架机器人的轨迹跟踪精度和整体性能.
主要方法:
- 提出了一种与未知的系统动态估计器 (USDE) 集成的新型漏斗控制 (FC) 策略.
- 为了管理复杂性,HDLLER动态模型被转化为布鲁诺夫斯基法典形式.
- 高增益观察器 (HGO) 用于状态重建,修改后的漏斗函数限制了跟踪错误.
主要成果:
- 拟议的FC-USDE战略有效地弥补了未知的内部和外部动态影响.
- 模拟和实验表明,在轨迹跟踪中,过渡和稳定状态性能得到了改进.
- 该方法成功地管理了高阶系统中的"复杂性爆炸".
结论:
- 开发的漏斗控制策略与未知的系统动态估计器提供了一个强大的解决方案,用于精确的轨迹跟踪在HDLLERs.
- 这种方法通过减轻不确定性和干扰来提高外骨机器人的性能.
- 通过模拟和步行实验验证,该方法显示出对外骨应用的巨大潜力.
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