Prescribed Instant Convergence Control for Multi-DOF Manipulators with Prescribed Performance
Bowei Yao, Xiaoning Shen, Chaoqun Song, Zhuang Liu, Yabin Gao, Jianxing Liu
Harbin Institute of Technology Yangtze River Delta Physics Research Center (China) Wuhu Hit Robot Technology Research Institute
内容与影响
This article addresses the trajectory tracking control problem for Multi-degree-of-freedom (Multi-DOF) manipulators subjected to unmodeled dynamics and external disturbances while ensuring prescribed performance. We introduce a prescribed instant convergence controller that stabilizes the system state to equilibrium at any user-specified instant, independent of the manipulator's initial state and parameter variations. Unlike traditional finite-time and fixed-time controllers, which provide only an upper bound on convergence time, the proposed controller achieves convergence at an arbitrarily chosen instant and allows for adjustable prescribed tracking errors. The effectiveness and robustness of the proposed control strategy are validated through simulations on a 7- DOF Franka manipulator, demonstrating superior performance in precise and timely trajectory tracking under varying conditions.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
回答优先基于摘要、文献信息与可获取全文;依据不足时会明确说明。
学术脉络
学科主题
工程Iterative Learning Control Systems
Robotic Mechanisms and Dynamics
参考文献 16
此处列出前 3 条