Adaptive Control of an Exothermic Chemical Reaction System Using Fuzzy Logic and Genetic Algorithms

Establishing suitable control of complex chemical reactions, a requirement in a number of industries, poses a difficult problem because of nonlinearities and frequently changing process dynamics. Researchers at the University of Alabama and the U. S. Bureau of Mines have developed a technique for producing adaptive fuzzy logic controllers (FLCs) that are capable of effectively managing such complex chemical systems. In this technique, a genetic algorithm (GA) is used to alter the membership functions employed by a conventional FLC, an approach that is contrary to the stratagem traditionally used to provide FLCs with adaptive capabilities in which the rule set is altered. The current approach is used to produce an adaptive GA-FLC for a particular system in which an exothermic chemical reaction is conducted. Specifically, formaldehyde is reacted with ammonia in a continuous stirred tank reactor to produce hexamine and water. Results indicate that FLCs augmented with GAs offer a powerful alternative to conventional process control techniques in the nonlinear, rapidly changing chemical systems commonly found in industry.