Fuzzy Modeling with Emphasis on Analog Hardware Implementation

In this paper, a new approach of fuzzy modeling with emphasis on analog hardware implementation is suggested. In the suggested approach, the input space of each input variable is partitioned independently through the modified form of fuzzy c-means (FCM) clustering algorithm to generate the membership functions. By considering all the possible combinations between the membership functions of the input variables and the cluster centers, the complete rule-base is generated through reference to the available input-output data. The output membership functions are taken to be singletons for easy and straightforward implementation in analog domain. The created rule-base is then optimized through the exhaustive search techniques suggested by the authors. The suggested approach has been applied on fuzzy controller data for rapid Nickel-Cadmium batteries charger developed [1]. The data for the batteries charger has been obtained through experimentation with an objective to charge the batteries as fast as possible. Special purpose analog modules, designed by the authors and realized with operational amplifiers (op-amps), diodes, resistors are considered for hardware implementation. The proposed fuzzy modeling design approach is described in Part I. Part II describes the synthesis and analog implementation.