Abstract
Abstract Proper selection of cooking times is one of the most important decision making tasks in batch pulp cooking. Duration of a batch depends on cooking conditions and must be chosen so that the Kappa number - a measure for pulp quality - reaches the desired value at the end of the batch. Due to the lack of appropriate industrial sensors for on-line Kappa measurements, Kappa can be determined only after cooking is over by means of analysis in the laboratory. Therefore, a model based system is developed for on-line Kappa estimation and control. The very heart of the system represents the estimation algorithm based on non-linear optimization. It combines a special purpose routine for approximate (but fast) optimum search and Gauss—Newton method for fine optimization. This paper surveys some relevant properties of the scheme such as model simplification, fine optimization, analysis of identifiability conditions and related numerical problems. A minimum variance Kappa controller is treated as well. Efficiency of the proposed scheme is confirmed by means of the simulated examples and results of practical implementation.
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