A genetic algorithm based approach to intelligent modelling and control of pH in reactors

Mwembeshi, M.M. and Kent, C.A. and Salhi, Said (2004) A genetic algorithm based approach to intelligent modelling and control of pH in reactors. Computers and Chemical Engineering, 28 (9). pp. 1743-1757. ISSN 0098-1354. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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The present work reports a novel genetic algorithm (GA) based strategy for designing efficient ‘global’ pH controllers in highly nonlinear neutralisation reactors, wherein linear internal model control (IMC) methodology and generic nonlinear compensators defined from acid–base principles are applied. In the study, the GA was used to optimise the IMC and nonlinear compensator parameters by evaluating a first-principles model developed to simulate a pH reactor. The proposed methodology was tested for assumed first- and second-order IMC transfer function models, initially for generality on a highly buffered pH reactor. A variant was developed for the problem of severe reactor nonlinearity, by including one of four defined nonlinear compensators in the optimisation process. Simulation results showed that the general use of the genetic algorithm based internal model control (GAIMC) strategy automated controller tuning that improved control performance, while its use with nonlinear compensators for the severely nonlinear reactor achieved tighter pH control for multiple operating regimes

Item Type: Article
Uncontrolled keywords: pH; Genetic algorithms; Modelling; Neutralisation; Internal model control
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Said Salhi
Date Deposited: 25 Sep 2008 12:27
Last Modified: 23 Apr 2014 10:23
Resource URI: https://kar.kent.ac.uk/id/eprint/5244 (The current URI for this page, for reference purposes)
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