renxiaolin
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- Name (Pinyin):renxiaolin
- Date of Birth:1985-08-13
- E-Mail:
- Teacher College:电气与电子工程学院
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- Paper Publications
Image-Based Visual Servoing Control of Robot Manipulators Using Hybrid Algorithm with Feature Constraints
Release time:2021-09-08 Hits:
- Affiliation of Author(s):电气与电子工程学院
- Journal:Complex & Intelligent Systems
- Funded by:国家自然科学基金项目
- Key Words:Adaptive dynamic programming · Neural networks · Optimal control · Visual servoing · Unknown dynamics
- Abstract:This paper investigates a feature tracking controlmethod for visual servoing (VS) manipulators adaptive dynamic programming (ADP)-based the unknown dynamics. The major superiority of ADP-based optimal control lies in that the visual tracking problem is converted to the feature tracking error control with optimal cost function. Moreover, an adaptive neural network observer is developed to approximate the entire uncertainties, which are utilized to construct an improved cost function. By establishing a critic neural network, the Hamilton–Jacobi–Bellman (HJB) equation is solved, and the approximate optimal error control policy is derived. The closed-loop VS manipulator system is verified to be ultimately uniformly bounded with the developed ADP-based feature tracking control strategy according to the Lyapunov theory. Finally, simulation results under various situations demonstrate that the proposed method achieves higher tracking accuracy than other methods, as well as satisfies energy optimal requirements.
- Co-author:李洪文,任晓琳
- First Author:renxiaolin
- Indexed by:Journal paper
- Page Number:1
- ISSN No.:2199-4536
- Translation or Not:no
- Date of Publication:2021-04-20