Control-oriented identification and uncertainty estimation for paper machines

A control-oriented identification and uncertainty estimation approach from input-output data is presented, for use in the design of control systems for paper machines. The application of this approach is demonstrated on a high fidelity simulator. An estimate of the process model along with the uncertainty bounds that describe the confidence limits of the model, consistent with the robust control theory, is obtained. These results can then be used to design a multivariable controller based on loop-shaping principles and guided by the estimated uncertainty bounds. The simulations demonstrate the suitability of the approach and illustrate that the technique can be used to provide high bandwidth performance for both servo and regulatory control.