Intelligent controller design for the flatness control in a cold rolling process

The flatness control in a cold rolling mill is an important subject because of the need for improvement in cold-rolled strip quality. It, however, is a difficult problem for a conventional approach to achieve since the cold rolling process is a highly nonlinear system in which many uncertain parameters are involved. The fuzzy controller for the flatness controller is designed by the heuristic approach that is based on the operator´s experience and knowledge gained in the experiments. The feature of a neural network´s learning and adapting ability is used for inverse modeling of the static model, and the error-decomposition network is developed as the inverse static model