Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/75048
Title: NN controller of the constrained robot under unknown constraint
Authors: Hu, S.
Ang Jr., M.H. 
Krishnan, H. 
Issue Date: 2000
Citation: Hu, S.,Ang Jr., M.H.,Krishnan, H. (2000). NN controller of the constrained robot under unknown constraint. IECON Proceedings (Industrial Electronics Conference) 3 : 2123-2128. ScholarBank@NUS Repository.
Abstract: In this paper, the problems faced in the constrained force control is studied (uncertainties in dynamic model and the unknown constraints). A neural network (NN) controller is proposed based on the derived dynamic model of robot in the task space. The feed-forward neural network is used to adaptively compensate for the uncertainties in the robot dynamics. Training signals are proposed for the feed-forward neural network controller. The NN weights are tuned on-line, with no off-line learning phase required. An on-line estimation algorithm is developed to estimate the local shape of the constraint surface by using measured data on the force and position of the end-effector. The suggested controller is simple in structure and can be implemented easily. Real-time Experiments are conducted using the five-bar robot to demonstrate the effectiveness of the proposed controller.
Source Title: IECON Proceedings (Industrial Electronics Conference)
URI: http://scholarbank.nus.edu.sg/handle/10635/75048
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