Prediction and Control System for Large-Scale Distributed Process Using Fuzzy Inference Method and Application to Prediction and Control System for Blast Furnace Heat Level

Abstract

In order to control a large-scale distributed process, it is important to predict output variation. A rule-based prediction model and a statistical one have been developed. Applying the fuzzy inference theory, we have connected these models and developed a total prediction model. In addition to these approaches, we have developed a heat level evaluation system using fuzzy inference. This system is used for evaluation and maintenance of a heat level prediction system. Using the predicted result, the action guide system to control the blast furnace heat level has been developed. By using this guidance system, the heat level can be controlled more accurately than before.