Fuzzy logic and applications

Abstract

As fuzzy logic is usually utilized for control and measurement in industries, this chapter first discusses fuzzy controls in the past, present, and future. A tutorial introduction to fuzzy logic and control is provided, along with practical examples of fuzzy control applications. In this chapter, we will first go through some of the significant turning points in the development of fuzzy logic technology. Following a brief overview of important ideas in fuzzy logic, we will examine a recent viewpoint on the foundation of two types of fuzzy rules. Finally, we look at some of the research that has been done to address different issues in the automatic identification of fuzzy rule-based models. Fuzzy idea lattices are being used to create fuzzy ontologies. Fuzzy formal contexts are used as the starting point for a range of proposed approaches to generate fuzzy idea lattices from them. This chapter examines two of these approaches, the one-sided threshold approach and the fuzzy closure operator approach, as well as the first comparison between the two. Following several basic instances, bioinformatics data, especially numerous gene annotation data files, are used. Our contribution to fuzzy logic is that it offers a systematic method for translating a rule base into nonlinear mapping. This chapter also discusses how fuzzy logic systems may be used to describe higher levels of hierarchical systems. We specifically consider three-level hierarchical systems in which the lowest level consists of the plant and conventional feedback controllers, the middle level performs supervisory operations to ensure the overall system’s stability, and the top level is a planning level that provides control targets for the lower levels and communicates with the environment. Differential equations are used to simulate it, while fuzzy logic systems are used to model the supervisory and planning levels. The benefit of this approach is that all levels are expressed in the same mathematical framework (owing to the dual role of fuzzy logic systems), allowing for theoretically rigorous analysis of hierarchical systems. Two case studies are presented, integrated planning and control of mobile robots and intelligent vehicle/highway systems.