Please use this identifier to cite or link to this item:
Title: Nonlinear Closed-Loop System Identification in The presence of Non-stationary Noise Source
Author: Aljamaan, Ibrahim
Advisor: Westwick, David
Foley, Michael
Keywords: Engineering--Electronics and Electrical
Abstract: In this dissertation, nonlinear identi fication approaches are presented that construct Wienerand Hammerstein models. These are block-oriented models consisting of a memoryless nonlinearity either preceded or followed by a linear filter, respectively. The algorithms were developed to handle several practical challenges common in chemical process control applications. These challenges include systems running in closed-loop, incorporating non-stationary process disturbances, and with possibly unstable plant dynamics. Identifi cation methods based on the prediction error method are developed to address these challenges. One of the main factors required for successful application of PEM algorithms is having a good initial estimate of the system under study. In this work, Instrumental Variable scheme is used to initialize the Hammerstein models, and a non-iterative overparameterized algorithm is developed to initialize the Wiener models. In all cases, the algorithms are developed theoretically, and then validated using Monte Carlo simulations. The closed-loop Hammerstein identifi cation algorithms are validated using data from differential equation based simulation of a continuous stirred tank reactor.
Appears in Collections:Electronic Theses

Files in This Item:
File Description SizeFormat 
ucalgary_2016_aljamaan_ibrahim.pdf5.22 MBAdobe PDFView/Open

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