Genetic algorithms and fuzzy control: a practical synergism for industrial applications

A way to automatically generate fuzzy controllers (FCs) that are optimized according to a merit figure is presented in this article. To achieve this task, a procedure based on hierarchical genetic algorithms (HGA) was developed. This procedure and the manner in which fuzzy controllers are codified into chromosomes is described. Resorting to this tool, several fuzzy controllers were constructed. The best three solutions obtained during simulation were selected for testing using an experimental prototype, which consists of an induction motor of variable load. These preliminary results are also included in the report. Based on these results, it is concluded that hierarchical genetic algorithms, though not the only, is a suitable artificial intelligence technique to face the problem of setting a fuzzy controller in a control loop without previous experience in controlling the plant. This is of help in many situations at industrial environments. (C) 2003 Elsevier B.V. All rights reserved.