A method of self-generating fuzzy rule base via genetic algorithm

It is known that the fuzzy control rules for a control system is always built by designers with trial and error and based on their experience or some experiments. This paper introduces a Genetic Algorithm (GA) based method to generate a satisfactory fuzzy rule base spontaneously. With the specific structure of the chromosome, the special mutation operation and the adequate fitness function, the proposed method with GA produces a fuzzy rule base with small number of rules, suitable placement of the premise's fuzzy sets and proper location of the consequent singletons. The generated fuzzy rule base can be the controller in a closed loop system to achieve some control objective or can be a fuzzy model to approximate an unknown nonlinear system. Finally, two examples are illustrated to show the effectiveness of the proposed method on the fuzzy control design and fuzzy modeling respectively.