Integrated identification and robust control for paper machines

An integrated modeling and robust multivariable control approach is presented for paper machines. An application of this approach is demonstrated on a high-fidelity simulator. Modeling relies on input-output data, collected from an identification experiment at the desired operating condition. 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. The results are used to design an 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.