基于非线性观测器的带有固定摄像头的柔性机械手视觉伺服和振动控制。

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Kai Li;Han Zhang;Hesheng Wang
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引用次数: 0

摘要

本文研究了当系统状态不可测且仅有图像反馈时柔性机械手的视觉伺服和振动抑制控制。基于奇异扰动理论,将柔性机械手的动态方程分解为慢速子系统和快速子系统。提出了基于使用列导数进行状态变换的非线性观测器,以同时估计不可测量的系统状态和未知的相机固有参数。然后,利用估计的状态分别在慢速子系统和快速子系统中设计基于图像的控制器,以同时调节特征点的图像位置和抑制柔性机械手的振动。在所提出的方法中,只需要视觉反馈来生成柔性机械手的控制输入,从而简化了控制器的实现。基于 Lyapunov 理论证明了所提控制方案的稳定性。最后,提供了一个柔性单链操纵器的实验结果,以证明所提控制方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonlinear Observer-Based Visual Servoing and Vibration Control of Flexible Robotic Manipulators With a Fixed Camera
This article studies the visual servoing and vibration suppression control for flexible manipulators when the system states are unmeasurable and only the image feedback is available. The dynamic equations of flexible manipulators are decomposed into the slow and fast subsystems based on the singular perturbation theory. The nonlinear observers based on the state transformation using the Lie derivatives are proposed to estimate the unmeasurable system states and unknown camera intrinsic parameters at the same time. Then, the image-based controllers utilizing the estimated states are, respectively, designed in the slow and fast subsystems to regulate the image positions of feature points and suppress the vibration of flexible manipulators simultaneously. In the proposed approach, only the visual feedback is required to generate the control input for flexible manipulators, which simplifies the controller implementation. The stability of the proposed control scheme is proved based on the Lyapunov theory. Finally, experimental results on a flexible single-link manipulator are provided to demonstrate the effectiveness of the proposed control approach.
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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