Genetic model reference adaptive control of shell heavy oil fractionator

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.