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

Utilises computational intelligence techniques, such as genetic algorithms (GAs) and multi-objective evolutionary algorithms (MOEAs), to design a Wiener-model controller for regulating the pH level in an acid-base titration process. A Wiener-model control structure comprises (i) an inverse model of the system nonlinearity and (ii) a simple linear controller. The inverse model serves to simplify the control problem by eliminating the bulk of the nonlinear characteristics from the pH control loop. A PID controller can then be used to control the linearised system. A GA was employed to identify the parameters of the inverse titration equation while the PID parameters were obtained by using a MOEA. Experimental results demonstrating the viability of the proposed methodology are presented.