Proportional correction rule for the control design of manufacturing systems using neural networks

Presents a control design for a particular class of manufacturing systems modeled by artificial neural networks. A dynamic implementation of manufacturing systems deduced from a modular approach of modeling using neural networks is described. An adaptive control is applied on the network model of the system. The proposed control is inspired from the learning property of neural networks. The obtained results are illustrated on an industrial manufacturing system.