Multistage control of a fuzzy system using a genetic algorithm

We consider multistage control of a fuzzy system, given by a fuzzy state transition equation, under fuzzy constraints and fuzzy goals. First, we briefly survey previous basic solution methods of dynamic programming and branch-and-bound, which basically require some “trickery”, and are plagued by low numerical efficiency, and then sketch Kacprzyk´s (1993) approach based on possibilistic interpolative reasoning aimed at enhancing the numerical efficiency but requiring a solution of a simplified auxiliary problem, and then some “readjusting” of the solution obtained. Then, we propose the use of a genetic algorithm. The real coding and specially defined operations of crossover, mutation, etc. are employed. The results obtained seem to be promising