ON A FUZZY MEASURE OF DIFFICULTY IN SYSTEM-IDENTIFICATION

The first step in any system identification procedure is the collection of data and its preliminary analysis. This step is generally neglected in the literature because in this step the maximum amount of human judgement, experience and decision-making is needed. In this paper Zadeh's fuzzy set theory is used to systematize this preliminary analysis of data. A fuzzy measure termed the ‘degree of difficulty’ (DOD) is derived, which quantifies in a fuzzy manner the difficulty and complexity involved in a system identification problem. The computation of DOD is based on the membership functions developed for nine fuzzy sets defined using nine characterizing properties of systems.