Analytical Theory of Fuzzy Control with Applications

The theme of this Special Issue is on Analytical Theory of Fuzzy Control with Applications. The theoretical development covered in this issue is focused on mathematical analysis and rigorous design methods for fuzzy control systems. Introduced in 1974, fuzzy control, as an emerging technology targeting industrial applications, has added a promising dimension to the existing domain of conventional control engineering. It is a common belief that when a complex physical system does not provide a precise or reasonably accurate mathematical model, particularly when the system description requires certain human experience in vague terms, fuzzy control methodology has some salient features and distinguished merits over many other approaches. Fuzzy control methods and algorithms, including many specialized software and hardware available on the market today, may be categorized as intelligent control since fuzzy control incorporates some kind of human expertise into its components (fuzzy sets, fuzzy logic, and fuzzy rule base). Using human knowledge in controller design is not only advantageous but oftentimes necessary. Even classical controller design incorporates human knowledge since what type of controller to use and how to determine the controller structure and parameters are largely depending on the decision and choice of the designer. The relatively new fuzzy control technology tends to be an alternative, rather than a replacement, of the existing control techniques such as classical controls and other intelligent controls (neural networks, expert systems, etc.). Together, they supply the control systems community with a more complete toolbox to deal with the complex, dynamic, and uncertain world. Fuzzy control technology is one of the many tools that are developed not only for elegant mathematical theories but, more importantly, for various practical problems with technical challenges. Compared with conventional approaches, fuzzy control utilizes more information from domain experts and relies less on mathematical modeling about a physical system. On one hand, fuzzy control theory can be heuristic Information Sciences 123 (2000) 161±162 www.elsevier.com/locate/ins