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Estimation and identification for machine direction control of basis weight and moisture

University of British Columbia

For the regulation of paper properties on a paper machine, measurements taken by a gauge tracing a zigzag pattern on the sheet must be decomposed into cross direction (CD) and machine direction (MD) signals. Researchers at the Pulp and Paper Centre, UBC, Vancouver, Canada have developed a decomposition algorithm (EIBMC) shown to give improved CD and MD estimates over previous methods. In this thesis the potential of the improved MD estimates for MD control is examined. Traditional scan-average MD estimates provide poor anti-aliasing and a sample rate fixed by the period of the scanning gauge. It is shown that the algorithm can be modified to provide estimates at any submultiple of the sensor sample rate with improved filtering flexibility. It is shown that CD estimation errors cause MD estimation errors proportional to the gradient of the CD errors. A scheme for reducing the CD and MD estimation errors due to poor filtering using a method involving sensor pre-filter design and manipulation of data in the EIBMC algorithm is presented. A computer simulation of a scanning sensor has been created and is used to illustrate the performance of the algorithm and anti-aliasing filter. A method is proposed for calculating the optimum sample rate for MD control based on the continuous-time average variance of the process output given the process statistics and time-delay. The method differs from previous methods in that it considers the effect of the anti-aliasing filter in obscuring the true output variance.

Thesis/Dissertation

application/pdf

2009-03-06

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http://hdl.handle.net/2429/5674

Electrical and Computer Engineering

University of British Columbia

UBCV

DSpace