Multivariable identification of a winding process by subspace methods for tension control

The challenging problem of multivariable tension control in winding systems is addressed in this paper. Two control configurations, the SS model and the ST model configurations (SS: speed-speed and ST: speed-torque), are considered and applied to a pilot winding plant. The relevance of using linear models in such multivariable systems is examined. Tension simulations based on a proposed linear ST model yield interesting results in both open and closed-loops. Emphasis is also laid on the applicability of subspace methods to winding tension state-space model identification. Such methods simplify the problem of multivariable identification by reducing the associated polynomial model structural identification to the easier problem of order estimation. It is shown that the design of a Linear Quadratic Gaussian (LQG) controller capable of ensuring efficient performance over the entire winding zone can be based on an 'average' state-space model identified around a nominal operating point.