Model Reference Control Based on Compensatory Fuzzy Neural Network for Gas Collectors of Coke Oven

Abstract

Abstract The pressure system of gas collectors of coke oven is a multivariable non-linear process. In this paper, a model reference adaptive control using the compensatory fuzzy neural network for the pressure system of gas collectors of coke oven is presented. The dynamics model of the fuzzy neural network of the system is identified by the adaptive compensatory fuzzy learning algorithm, which can be employed as the identifier of the system. Another fuzzy neural network is trained to learn the inverse dynamics of the pressure system of gas collectors of coke oven so that it can be used as a nonlinear controller. The simulation results testify that the model obtained is satisfied and the control is effective.