The Application of Fuzzy Neural Networks to the Temperature Control System of Oil-Burning tunnel Kiln

摘要

Fuzzy control is a human-imitating control technique which is independent on mathematical model of plants. It utilizes priori knowledge to carry out approximate reasoning. But it is lack of the ability of self-tuning or self-learning in industrial applications. The temperature control process of oil-burning Tunnel kiln is a multivariable and nonlinear dynamic system. Facing this plant, this paper presents a fuzzy neural network control strategy which is able to enhance the capacity of self-learning of fuzzy control rules, based on the self-learning ability of neural networks. Simulation research and physical analog experiment prove the feasibility of this control strategy.