Fuzzy control of pH using genetic algorithms

Abstract

Abstruct- Establishing suitable control of pH, a requirement in a number of mineral and chemical industries, poses a difficult problem because of inherent nonlinearities and frequently changing process dynamics. Researchers at the U.S. Bureau of Mines have developed a technique for producing adaptive fuzzy logic controllers (FLC’s) that are capable of effectively managing such systems. In this technique, a genetic algorithm (GA) alters the membership functions employed by a conventional FLC, an approach that is contrary to the tactic generally used to provide FLC’s with adaptive capabilities in which the rule set is altered. GA’s are search algorithms based on the mechanics of natural genetics that are able to rapidly locate near-optimal solutions to difficult problems. The Bureau-developed technique is used to produce an adaptive GA-FLC for a laboratory acid-base experiment. Nonlinearities in the laboratory system are associated with the logarithmic pH scale (pH is proportional to the logarithm of HJO’ ions) and changing process dynamics are introduced by altering system parameters such as the desired set point and the concentration and buffering capacity of input solutions. Results indicate that FLC’s augmented with GA’s offer a powerful alternative to conventional process control techniques in the nonlinear, rapidly changing pH systems commonly found in industry.