A new adaptive fuzzy neural force controller for robots manipulator interacting with environments

Zong Yu Jhan, Ching Hung Lee, Chih Min Lin

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

In this paper, a fuzzy neural network-based adaptive force control scheme for an it-link robot manipulator under an unknown environment is proposed. The dynamics model of the robot manipulator and the environment stiffness coefficient are assumed to be not exactly known in applications. Therefore, the traditional adaptive impedance force controller is not valid. In this study, the fuzzy neural systems (FNSs) are adopted to estimate the model of robot manipulator to propose an adaptive scheme to accomplish the tracking control problem. Based on the Lyapunov stability theory, the stability of the robot manipulator is guaranteed and the corresponding update laws of FNSs' parameters and stiffness coefficient of the environment can be obtained. Finally, simulation results of two-link robot manipulator contact with environment are introduced to illustrate the performance and effectiveness of our approach.

原文English
主出版物標題Proceedings of 2015 International Conference on Machine Learning and Cybernetics, ICMLC 2015
發行者IEEE Computer Society
頁面572-577
頁數6
ISBN(電子)9781467372213
DOIs
出版狀態Published - 30 11月 2015
事件14th International Conference on Machine Learning and Cybernetics, ICMLC 2015 - Guangzhou, China
持續時間: 12 7月 201515 7月 2015

出版系列

名字Proceedings - International Conference on Machine Learning and Cybernetics
2
ISSN(列印)2160-133X
ISSN(電子)2160-1348

Conference

Conference14th International Conference on Machine Learning and Cybernetics, ICMLC 2015
國家/地區China
城市Guangzhou
期間12/07/1515/07/15

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