任务优化用于固定时间控制间歇的人机交互与时间变化的指数和系数的间歇的人机交互
IEEE transactions on cybernetics
|January 23, 2026
概括
本研究介绍了一种新的等级固定时间事件触发优化算法,用于人机交互. 该算法增强了任务优化,并通过允许人类操作员保密地选择帕雷托解决方案来确保数据安全.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制理论 控制理论
- 人与机器人的交互
背景情况:
- 间歇的人机交互需要高效的任务优化.
- 在人机协作过程中确保数据保密至关重要.
- 固定时间控制提供精确的收特性.
研究的目的:
- 开发一种任务优化算法,用于间歇性人机交互中的固定时间控制.
- 为了提高收轮塑造的灵活性,使用利亚普诺夫稳定条件.
- 提出一个安全,以人为本的优化方案.
主要方法:
- 用时间变化的指数和系数推导莱普诺夫固定时间稳定性条件.
- 建议一个层次的固定时间事件触发优化 (HFTEO) 算法.
- 实施以人为本的任务信息保密计划.
主要成果:
- 新的利亚普诺夫稳定性条件在系统设计中提供了更大的灵活性.
- HFTEO算法有效地优化了间歇性人机交互中的任务.
- 这种以人为本的方案成功地确保了任务信息的保密性和安全性.
结论:
- 拟议的Lyapunov稳定条件提高了人机系统的控制设计.
- HFTEO算法为任务优化提供了一种有效和安全的方法.
- 这项工作通过安全,优化的控制来推进间歇性人机交互.
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