A fuzzy logic programming environment for real-time control

Abstract

Expert systems based on fuzzy logic inferencing have been shown to be effective in controlling complex processes. The experiences of human operators are naturally captured as linguistic fuzzy control rules. This paper describes a programming environment being developed to facilitate the implementation of fuzzy control systems that allow a user to easily describe a set of fuzzy rules, graphically edit the fuzzy variable definitions, and verify the rules through simulation. In an actual control system, the rules will reside in and be processed by a special-purpose chip for fuzzy logic inferencing. An object-oriented approach to the programming environment naturally models this hardware architecture. Each set of rules is associated with a chip object simulated in software. The content of the chip object is changed as the rules are modified. When the simulation results are satisfactory, the content of the simulated chip can be copied directly into the hardware chip for real-time applications. A complex controller that involves multiple domains of expertise can be developed by first focusing on component chip objects and then interconnecting the components. The ability to translate linguistic rules into practical implementations is a unique and useful feature of this environment.