Design Fuzzy Controller for the Ball Positioning System Based on the Knowledge Acquisition and Adaptation
Hyeon Bae, Jae Ryong Jung, Sungshin Kim · Journal of Korean institute of intelligent systems · 2001
Industrial processes are normally operated by skilled humans who have the cumulative and logical information about the systems. Fuzzy control has been investigated for many applications. Intelligent control approaches based on fuzzy logic have a chance to include human thinking. This paper represents modeling approach based upon operators knowledge without mathematical model of the system and optimize th controller. The experimented system is constructed for sending a ball to the goal position using wind of two DC motors in the predefined path. A vision camera to mimic human eyes detects the bal position. The system used in this experiment could be hardly modeled by mathematical methods and could not be easily controlled by conventional manners. The controller in designed based on the input-output data and experimental knowledge obtained by trials, and optimized under the system is driven in the abnormal condition with unconsidered noise, the new optimal operating parameters could be defined by adjusting membership functions. Thus, this technique could be applied in industrial fields.