| 引用本文: | 李绍宇,王福杰,钟金明,李醒,郭芳,秦毅,孙泽文.具有边界值未知控制增益和输出约束的多机械臂有限时间控制[J].控制理论与应用,2025,42(9):1827~1837.[点击复制] |
| LI Shao-yu,WANG Fu-jie,ZHONG Jin-ming,LI Xing,GUO Fang,QIN Yi,SUN Ze-wen.Finite time control for multi-robot rrms with unknown boundary control gains and output constraints[J].Control Theory & Applications,2025,42(9):1827~1837.[点击复制] |
|
| 具有边界值未知控制增益和输出约束的多机械臂有限时间控制 |
| Finite time control for multi-robot rrms with unknown boundary control gains and output constraints |
| 摘要点击 2115 全文点击 175 投稿时间：2023-06-12 修订日期：2025-02-12 |
| 查看全文 查看/发表评论 下载PDF阅读器 HTML |
| DOI编号 10.7641/CTA.2024.30404 |
| 2025,42(9):1827-1837 |
| 中文关键词 未知控制增益 多机械臂系统 积分障碍Lyapunov函数 有时间控制 |
| 英文关键词 unknown control gains multi-robot arm systems integral barrier Lyapunov functions finite-time control |
| 基金项目 国家自然科学基金项目(62203116,62103106,62273095), 广东省基础与应用基础研究基金面上项目(2024A1515010222),广东省教育厅特色创新 项目重点领域项目(2022KTSCX138,2022ZDZX1031),东莞市社会发展科技重点项目(20231800935882),辽宁省自然科学基金项目(2022–KF 21–06), 广东省基础与应用基础研究基金联合基金(粤莞)项目(2021A1515110075)资助. |
|
| 中文摘要 |
| 针对具有边界值未知控制增益和输出全状态约束的多机械手协同搬运系统,提出一种基于积分障碍Lyap
unov函数和径向基函数神经网络的鲁棒有限时间分布式自适应控制算法.该算法采用自适应径向基函数神经网络
逼近系统的未知项,利用积分型障碍Lyapunov函数保证输出的位置和速度信号不违背约束,并通过包含控制增益未
知下确界的Lyapunov函数和在控制律中引入辅助项调节参数,在无需获取边界值信息的情况下实现了对未知控制
增益的补偿.最后,结合有限时间稳定理论和反步式控制框架,实现了系统的位置、速度和内力误差在有限时间内
有界收敛. |
| 英文摘要 |
| In this study, we propose a robust finite-time distributed adaptive control algorithm for multi-robot arm
cooperative manipulation systems with unknown boundary control gains and full-state output constraints, based on integral
barrier Lyapunov functions and radial basis function neural networks. The proposed algorithm employs adaptive radial basis
function neural networks to approximate the unknown terms of the system, while the integral barrier Lyapunov function
ensures that the position and velocity output signals do not violate constraints. By incorporating a Lyapunov function
with an unknown lower bound for control gain and introducing auxiliary adjustment parameters in the control law, the
compensation for unknown control gains is achieved without obtaining boundary value information. Finally, by combining
f
inite-time stability theory and a backstepping control framework, the position, velocity, and internal force errors of the
system are proven to converge within a finite time. |
|
|
|
|
|