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A Fuzzy-Neural Control for Uncertainty Compensation of Robot Manipulator  

박세준 (목원대학교 IT공학과)
양승혁 (도담시스템즈㈜ 서브시스템 H/W 엔지니어)
황문구 (목원대학교 IT공학과)
양태규 (목원대학교 IT공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.7, no.8, 2003 , pp. 1759-1766 More about this Journal
Abstract
This paper proposes a neuro­fuzzy controllers for trajectory tracking control of robot manipulators. The computed torque method is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. Therefore, the proposed controller is used to compensate the uncertainties of robot manipulators. In the neuro­fuzzy controllers, the number of fuzzy rules used forty­nine. The effectiveness of the proposed controllers is demonstrated by computer simulations using two­link robot manipulator, As a result, it is confirmed that the output of the proposed neuro­fuzzy controllers can efficiently decrease the uncertainties of robot manipulator.
Keywords
neuro­fuzzy; tracking; compensate; uncertainties;
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