FKBC Design Parameters

Abstract

This chapter introduces the principal design parameters of a FKBC. These include scaling factors, fuzzification and defuzzification methods, rule base and membership function construction and representation. Furthermore, we discuss the relevance of the different design parameters with respect to the performance of a FKBC. Different design options for particular parameters are presented. Choice of membership functions, defuzzification methods, inference engine, and form and meaning of rules are considered in detail. Design parameters like fuzzification, and checking the properties of the rule base are only mentioned, since these were already described in Chapter 2. Other design parameters like scaling factors, derivation of rules, tuning of the FKBC, and stability analysis, are only informally discussed or just mentioned. Thus, this chapter gives a general view of the FKBC design problem and prepares the reader for the formal treatment and/or presentation of systematic techniques for rule derivation and scaling factors determination (Chapter 4), FKBC tuning and adaptation (Chapter 5), and stability analysis (Chapter 6).