De Vaal, Philip L.2022-08-172022-08-171998-091998-04*https://repository.up.ac.za/handle/2263/86835Dissertation (MSc (Control Engineering))--University of Pretoria, 1998.The aim of this study was to test the applicability and utility of linear multivariable robust analysis techniques to a typical chemical process control problem. The fundamental issue in feedback control is robustness in the face of uncertainty. The integrated nature of the process studied leads to interaction between process variables, necessitating a multivariable approach. It was found that robust analysis techniques provide a useful source of information: the traditional use of safety margins to ensure robustness based on rules of thumb can be replaced by precisely calculated margins. Robustness of a feedback loop with regard to stability and performance is evaluated by considering an upper bound on a scalar-valued function of frequency, namely the structured singular value. An obvious requirement for the testing of robustness is a description bounding the expected uncertainty. A description encompassing the entire range of possible plant operating conditions using a linear nominal plant model with associated bounded perturbation for the system under study, was derived. The uncertainty description used, independent norm-bounded additive uncertainty in the transfer function matrix elements, reduces this multivariable description to a number of single input single output process identification problems. A novel algorithm was used to calculate the least conservative nominal plant model with norm-bounded uncertainty description. The calculation algorithm employed for robust analysis requires that the problem statement be given a specific structure, the so called ~-structure. It was found that it is possible to transform the evaluation of robust stability and robust performance to this structure. The major weakness of robust analysis techniques are strong dependence on the validity and tightness of the uncertainty description. Techniques exist which allow a tighter linear description of plant uncertainty than the technique used in this study. It is however so that a significant portion of the uncertainty stems from the fact that a linear model is used to describe an inherently (known) nonlinear plant. It is believed that linear robust analysis techniques provide a significant aid to theen© 2021 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.UCTDRobust controlProcess controlStructured singular valueTriple-effect evaporatorMulti-variable controlNorm-bounded uncertaintyAdditive uncertaintyProcess modellingDissertation92296123