Abstract

This paper describes the intelligent control systems implemented by new technologies about processing information such as fuzzy logic and fuzzy neuron. This paper is constructed by the basic concept of fuzzy logic and artifical neural networks, and they are then combined to share the ability for modifying the intelligence of control systems working in uncertain, imprecise. And noisy environments. Systems desired working in such these environments, systems must be build up by the four main elements: fuzzification strategies, knowledge base, fuzzy reasoning mechanism, and defuzzification strategies. These basic elements associated with the basic concepts of artificial neural networks forms the fuzzy neuron systems trained by using different learning modes.