Design of fuzzy Logic Systems for Engineering Uses

Abstract

Fuzzy logic systems have become indispensable in engineering because they can handle uncertainty and complex decision-making. By extending classical binary logic, fuzzy logic allows for gradual truth values between 0 and 1. In this context, we explore the design process of fuzzy logic systems, including defining linguistic variables, membership functions, and fuzzy rules. These systems find applications in control, pattern recognition, decision support, and robotics. Challenges such as rule-based complexity and interpretability are discussed, along with future directions for research. Among the most effective methods available today for creating complex control systems is fuzzy logic. This has a very straightforward explanation. Fuzzy logic serves such applications well since it mimics human decision-making and can produce exact solutions from specific or approximate data. It closes a significant gap in engineering design methodologies that solely quantitative approaches still need to be included. Overall, fuzzy logic systems offer a flexible and robust framework for solving real-world engineering problems. Fuzzy logic provides a mathematical framework that handles uncertainty and imprecision and has gained significant prominence in engineering applications. In this paper, we explore the relevance of fuzzy logic in various engineering domains and discuss its impact on system design and decision-making.