Breadcrumb

 
 

On-line adaptive control of dynamic systems preceded by hysteresis via neural networks

Title:

On-line adaptive control of dynamic systems preceded by hysteresis via neural networks

Chen, Weihua (2004) On-line adaptive control of dynamic systems preceded by hysteresis via neural networks. Masters thesis, Concordia University.

[img]
Preview
PDF - Accepted Version
3021Kb

Abstract

This thesis deals with on-line adaptive control of a class of dynamic systems preceded by backlash-like hysteresis nonlinearities via dynamic neural networks. A three layer recurrent neural network called the diagonal recurrent neural network (DRNN) is applied to construct the hysteresis inverse compensator (DRNNC) to remove the effect of hysteresis. An on-line learning algorithm called the dynamic back propagation (DBP) algorithm is developed to train the DRNN. Based on the cancellation of hysteresis effect, an adaptive tracking control architecture, which is constructed through the combination of sliding mode and Gaussian network (GNNC), is then proposed. The diagonal recurrent neural network compensator (DRNN) and Gaussian network controller (GNNC) are trained at the same time since DRNN requires fewer weights, and less training time, and still preserves the dynamic characteristics, which allow the DRNN model to be used for on-line application. The performance of this control structure is illustrated through simulations with example system.

Divisions:Concordia University > Faculty of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Chen, Weihua
Pagination:xiv, 134 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Date:2004
Thesis Supervisor(s):Cun-Yi, Su
ID Code:7986
Deposited By:Concordia University Libraries
Deposited On:18 Aug 2011 14:12
Last Modified:18 Aug 2011 14:12
Related URLs:
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Document Downloads

More statistics for this item...

Concordia University - Footer