Fuzzy reinforcement learning control for compliance tasks ofrobotic manipulators

Tzafestas S.G.; Rigatos G.G.

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Fuzzy reinforcement learning control for compliance tasks ofrobotic manipulators

机译：机器人的依从性任务的模糊强化学习控制

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A fuzzy reinforcement learning (FRL) scheme which is based on thenprinciples of sliding-mode control and fuzzy logic is proposed. The FRLnuses only immediate reward. Sufficient conditions for the convergence ofnthe FRL to the optimal task performance are studied. The validity of thenmethod is tested through simulation examples of a robot which deburrs anmetal surface

机译：提出了一种基于滑模控制原理和模糊逻辑的模糊强化学习（FRL）方案。 FRLnuses仅立即获得奖励。研究了使FRL收敛到最佳任务性能的充分条件。然后通过机器人对金属表面去毛刺的仿真示例测试了该方法的有效性

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《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》 |2002年第1期|p.107-113|共7页
作者
Tzafestas S.G.; Rigatos G.G.;
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原文格式 PDF
正文语种 eng
中图分类自动化基础理论;
关键词
compliance control; fuzzy control; fuzzy logic; intelligent control; learning (artificial intelligence); manipulators; variable structure systems; FRL scheme; compliance tasks; fuzzy reinforcement learning; fuzzy reinforcement learning control; hybrid hierarchical;

机译：合规控制;模糊控制;模糊逻辑;智能控制;学习（人工智能）;机械手;可变结构系统;FRL方案;合规性任务;模糊强化学习;模糊强化学习控制;混合层次;

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3. H_∞ reinforcement learning control of robot manipulators using fuzzy wavelet networks [J] . Chuan-Kai Lin Fuzzy sets and systems . 2009,第12期

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4. Combined learning and identification techniques in the control ofrobotic manipulators [C] . Aicardi, M., Casalino, G., Bartolini, G. 1993 International Joint Conference on Neural Networks, 1993. IJCNN '93-Nagoya, 1993 . 2001

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5. Impedance control of a manipulator using a fuzzy model reference learning controller. [D] . Strawson, Michael R. 2006

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6. Variable Admittance Control Based on Fuzzy Reinforcement Learning for Minimally Invasive Surgery Manipulator [O] . Zhijiang Du, Wei Wang, Zhiyuan Yan, 2017

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Fuzzy reinforcement learning control for compliance tasks ofrobotic manipulators

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