Title: Genetic model reference adaptive control of shell heavy oil fractionator

Authors: Dauda Olurotimi Araromi; Aminah Abolore Sulayman; Olajide Olukayode Ajala

Addresses: Department of Chemical Engineering, Ladoke Akintola University of Technology, P.M.B 4000 Ogbomoso, Oyo State, Nigeria ' Department of Chemical Engineering, Ladoke Akintola University of Technology, P.M.B 4000 Ogbomoso, Oyo State, Nigeria ' Department of Chemical Engineering, Ladoke Akintola University of Technology, P.M.B 4000 Ogbomoso, Oyo State, Nigeria

Abstract: Fractionators are characterised by high nonlinear dynamic behaviour, strong loop interactions and model uncertainties. Relative gain array (RGA) was used to determine the level of loop interaction. Dynamic decoupler was used to remove the interactions which were obtained using feed-forward design technique. A feedback control system is designed for the dynamic decoupled plant using Ziegler-Nichols tuned proportional integral (PI) controller. A genetic model reference adaptive controller (GMRAC) is designed to control the fractionator using a second order reference model and adaptation mechanism based on genetic algorithm (GA). Genetic algorithm uses real-coded data generation for optimisation. Comparison is made with the PI controller. Performance indices were based on settling time, rise time and overshoot.

Keywords: genetic model reference adaptive controller; GMRAC; adaptive control; PI; MATLAB; relative gain array; RGA; shell heavy oil fractionator; SHOF.

DOI: 10.1504/IJNDC.2019.098645

International Journal of Nonlinear Dynamics and Control, 2019 Vol.1 No.3, pp.231 - 254

Received: 30 Apr 2018
Accepted: 05 May 2018

Published online: 25 Mar 2019 *

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