Performance Optimization of Large Control Systems – Case Study on a Continuous Pulp Digester
| Authors: | Halmevaara Kalle, Helsinki University of Technology, Finland
Hyötyniemi Heikki, Helsinki University of Technology, Finland |
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| Topic: | 6.1 Chemical Process Control |
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| Session: | Advances in Automation in Pulp Industry |
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| Keywords: | Multivariable control systems, Large-scale systems, Process control, Pulp Industry, Multiple-criterion optimization, Iterative methods, Regression analysis, Complex systems |
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Abstract
This paper presents an example application of a novel multivariate control parameter tuning method, called Iterative Regression Tuning (IRT), on a simulator of continuous pulp digester. IRT is a data based method in which multivariate regression and iterative optimization methods are utilized in the parameter tuning. In the test case seven PI controllers and two model based controllers were tuned simultaneously and six user-defined quality measures were set as optimization targets. Encouraging results on the process performance improvement were obtained and the method proved a clear potential for optimization of large industrial systems.
