Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/54171
Title: A framework for robust neural network-based control of nonlinear servomechanisms
Authors: Lee, T.H. 
Wang, Q.G. 
Tan, W.K. 
Issue Date: Oct-1994
Source: Lee, T.H.,Wang, Q.G.,Tan, W.K. (1994-10). A framework for robust neural network-based control of nonlinear servomechanisms. Mechatronics 4 (7) : 693-712. ScholarBank@NUS Repository.
Abstract: A framework for robust neural network-based control of nonlinear servomechanisms is proposed and presented. This framework utilizes a general controller structure that comprises a nonlinear compensation block and a robust control block. Two different strategies for designing the control laws for these are discussed and it is shown that uniform stability of the overall system even in the presence of modeling mismatches and non-parametric uncertainly is achieved. The effectiveness of this proposed framework is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load. © 1994.
Source Title: Mechatronics
URI: http://scholarbank.nus.edu.sg/handle/10635/54171
ISSN: 09574158
Appears in Collections:Staff Publications

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

Page view(s)

30
checked on Dec 14, 2017

Google ScholarTM

Check


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