Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/61763
Title: Adaptive neural network controller design for flexible joint robots using singular perturbation technique
Authors: Ge, Shuzhi S. 
Postlethwaite, Ian
Issue Date: 1995
Source: Ge, Shuzhi S.,Postlethwaite, Ian (1995). Adaptive neural network controller design for flexible joint robots using singular perturbation technique. Transactions of the Institute of Measurement and Control 17 (3) : 120-131. ScholarBank@NUS Repository.
Abstract: In this paper, an adaptive neural network controller is presented for flexible joint robots using Singular Perturbation techniques by modelling the elastic forces as the fast variables and link variables as slow variables. The neural network controller is to control the slow dynamics in order to eliminate the tedious preliminary computation of the regressor matrix. Unlike many neural network (NN) controllers in the literature, inverse dynamical model evaluation is not required and no time-consuming training process is necessary except for initialising the NNs based on approximate function values at the initial posture at time t = 0. It can be shown that the controller can control the system successfully by intensive computer simulation tests.
Source Title: Transactions of the Institute of Measurement and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/61763
ISSN: 01423312
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

14
checked on Dec 7, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.