Evolutionary based optimisation of multivariable fuzzy control system of a binary distillation column

Abstract

Genetic Algorithms (GA), Simulated Annealing (SA) and Particle Swarm Optimisation (PSO) are population based stochastic search algorithms that categorised into the taxonomy of evolutionary optimisation. These methods have been employed independently to tune a fuzzy controller for maintaining the product compositions of a binary distillation column. An analytical investigation has been conducted to distinguish the optimal tuning approach of the controller among these techniques. Based on simulation results, particle swarm optimisation approach combined with the fuzzy controller is identified as a comparatively better configuration regarding its performance index and computational efficiency.