SIMULATION OF FUZZY SHAPE CONTROL FOR COLD-ROLLED STRIP WITH RANDOMLYIRREGULAR STRIP SHAPE

Control of cross-sectional cold rolled strip shapes is an important su bject in rolling mill because of improvement of cold-rolled strip qual ities. However, it is not easy to tackle the problem in a mathematical form since the cold rolling process is a highly nonlinear system in w hich many parameters are involved. In this study, a fuzzy control algo rithm was developed to control the randomly irregular cold-rolled stri p. The currently developed fuzzy control algorithm consists of two par ts: the first part calculates the changes of work and intermediate rol ls bender forces based on the symmetric part of the irregular cold rol led strip shape, and the second part calculates the weighting factors based on the asymmetric part in order to modify the pre-determined rol l bender forces. As a result of this, bender forces applied at both si des of the cold-rolled strip will be different. The fuzzy rules were f ormulated based on the production data to control the delivery shape a t the last stand of a tandem cold mill. Tn order to simulate continuou s shape control, the fuzzy controller was Linked with an emulator. The emulator was constructed by neural network theory based on the same p roduction data. According to calculated bender forces of work and inte rmediate rolls from the developed fuzzy controller, the emulator predi cted the changes of the randomly irregular cold rolled strip shape. Th e developed fuzzy controller and emulator simulated the cold rolling p rocess until the randomly irregular shape converged to a tolerable ran ge to produce a uniform cross-sectional strip shape. The simulations w ere carried out on IBM PC 486. The results obtained from the simulatio ns were reasonable for various randomly irregular strip shapes. Thus, the developed fuzzy control system might be useful in controlling the cold rolling process without introducing manual control.