An application of genetic algorithm for designing a Wiener-model controller to regulate the pH value in a pilot plant

Abstract

The work described in this paper aims at utilising computational intelligence techniques, such as genetic algorithm (GA) and multi-objective evolutionary algorithm (MOEA), to design a Wiener-model controller for regulating the pH level in an acid-base titration process. A Wiener-model control structure comprises of (i) an inverse model of the system non-linearity, and (ii) a simple linear controller. The inverse model serves to simplify the control problem by eliminating the bulk of the non-linear characteristics from the pH control loop. A Proportional-plus-Integral-plus-Derivative controller can then be used to control the linearised system. GA was employed to identify the parameters of the inverse titration equation while the PID parameters were obtained using MOEA. Experimental results demonstrating the viability of the proposed methodology are presented.