Automatic design of fuzzy logic controller using a genetic algorithm—to predict power requirement and surface finish in grinding

We have developed a method for automatic design of fuzzy logic controller (FLC) using a genetic algorithm (GA). The performance of an FLC depends on its knowledge base (KB), which consists of membership function distributions (also known as data base) and rule base. To design a proper KB of the FLC, the designer should have a thorough knowledge of the process to be controlled. Sometimes, it becomes difficult to gather knowledge of the process beforehand. Thus, designing the proper KB of an FLC is not an easy task. In this paper, a new approach for designing the KB of an FLC (using a GA) is proposed and its effectiveness is compared to a previous approach based on GA-fuzzy combination for making predictions of power requirement and surface finish in grinding (a machining process to obtain smooth surface on the work).