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
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摘要与影响
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.
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工程Iterative Learning Control Systems
Robotic Mechanisms and Dynamics
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