Please use this identifier to cite or link to this item:
Title: Adaptive neural network control for smart materials robots using singular perturbation technique
Authors: Ge, S.S. 
Lee, T.H. 
Wang, Z.P. 
Keywords: Adaptive control
Neural networks
Singular perturbation
Smart materials robots
Issue Date: Jun-2001
Citation: Ge, S.S.,Lee, T.H.,Wang, Z.P. (2001-06). Adaptive neural network control for smart materials robots using singular perturbation technique. Asian Journal of Control 3 (2) : 143-155. ScholarBank@NUS Repository.
Abstract: An adaptive neural network controller is presented for smart materials robots using singular Perturbation techniques by modeling the flexible modes and their derivatives as the fast variables and link variables as slow variables. The neural network (NN) controller is to control the slow dynamics in order to eliminate the need for the tedious dynamic modeling and the error prone process in obtaining the regressor matrix. In addition, inverse dynamic model evaluation is not required and the time-consuming training process is avoided except for initializing the NNs based on the approximate function values at the initial posture at time t=0. The smart materials bonded along the links are used to active suppress the residue vibration. Simulation results have shown that the controller can control the system successfully and effectively.
Source Title: Asian Journal of Control
ISSN: 15618625
Appears in Collections:Staff Publications

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

Page view(s)

checked on Jan 11, 2021

Google ScholarTM


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