A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented in this paper. The premise of an implication is the description of fuzzy subspace of inputs and its consequence is a linear input-output relation. The method of identification of a system using its input-output data is then shown. Two applications of the method to industrial processes are also discussed: a water cleaning process and a converter in a steel-making process.

So called fuzzy control has been developed for the purpose of realization of a man-like controller with the aid of computer. However, most of fuzzy controllers have two very important problems. First is a defect of the reasoning algorithm. Second is a way to acquire control rules, particulaly the precise parameters in the rules. In this Daper considering the above problems, we propose a realistic fuzzy reasoning algorithm and a method to identify control rules from human operators actual control actions. Further we examine the performance of the proposed algorithm by applying it to water cleaning process control.