基于事件的自适应跟踪控制用于具有延迟位置约束和未知的反响类歇斯底里症的机器人系统
Siwen Hao1, Yingnan Pan1, Yuting Zhu2
1College of Control Science and Engineering, Bohai University, Jinzhou, 121013, Liaoning, China.
ISA transactions
|August 13, 2023
概括
本研究介绍了一种基于事件的自适应控制,用于面临未知的反响类歇斯底里 (BLH) 和位置约束的机器人系统. 新方法确保有界系统信号,改善跟踪控制性能.
科学领域:
- 机器人和控制系统 机器人和控制系统
背景情况:
- 机器人系统经常面临诸如未知的反响类歇斯底里 (BLH) 和延迟位置约束等挑战,使精确的跟踪控制复杂化.
- 传统的屏障莱普诺夫函数方法依赖于假设,这些假设限制了它们对具有位置约束的系统的适用性.
研究的目的:
- 为n-link机器人系统提出基于事件的自适应跟踪控制方案.
- 解决未知的BLH和延迟位置限制,而不违反预先规定的时间限制.
- 为了删除传统的障碍莱普诺夫函数方法中常见的假设条件.
主要方法:
- 转换误差与不对称的利亚普诺夫函数相结合,用于控制设计.
- 纳斯姆函数被用来抵消未知的BLH的影响.
- 实现事件触发机制以优化网络带宽使用.
- 利亚普诺夫理论是确保信号局限性的基础.
主要成果:
- 拟议的控制策略确保在用户预先指定的时间后不会违反位置约束.
- 未知BLH的不良影响得到了有效的抵消.
- 事件触发机制节约了网络带宽资源.
- 机器人系统的所有信号在指定的条件下被证明是受限的.
结论:
- 开发的基于事件的自适应跟踪控制方案对具有未知的BLH和延迟位置约束的n-link机器人系统有效.
- 该方法通过节约网络资源和消除限制性假设,提高了稳定性和效率.
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