An adaptive process control system based on fuzzy logic and genetic algorithms

In today's highly competitive economic environment, industries must develop new and innovative control strategies in order to compete in a global market. One such innovative control strategy has led to the development of fuzzy logic controllers (FLCs). However, the performance of FLCs, like that of most other control strategies, can be severely limited by inadequate feedback. Researchers at the US Bureau of Mines have developed an approach in which genetic algorithms (GAs) can be used to enhance otherwise inadequate feedback from industrial systems. GAs are search algorithms based on the mechanics of natural genetics. They rapidly locate near optimum solutions in poorly behaved search spaces such as those associated with the enhancement of controller feedback. The effectiveness of the Bureau's approach is demonstrated using two systems: a physical pH titration system and a simulated chemical processing system.