Impact of model plant mismatch on performance of control systems: An application to paper machine control |
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| Affiliation: | 1. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver BC;2. Department of Chemical and Biological Engineering, University of British Columbia, Vancouver BC;3. Department of Mathematics, University of British Columbia, Vancouver BC;4. Honeywell Process Solutions, North Vancouver BC;1. University of Bayreuth, Mathematical Institute, Germany;2. Ruhr-University Bochum, Institute of Automation and Computer Control, Germany;1. Universidade Federal de Santa Catarina, Departamento de Automação e Sistemas, 88040-900 Florianópolis, SC, Brazil;2. Dpto. de Informática, Universidad de Almería - CIESOL, Campus de Excelencia Internacional Agroalimentario, ceiA3. Crta. Sacramento s/n, 04120 La Cañada, Spain;1. German Aerospace Center (DLR), Oberpfaffenhofen, Germany;2. AIRBUS Flight Control Systems, Toulouse, France;3. DEIMOS-SPACE S.L.U., Madrid, Spain (now with the University of Bristol) |
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| Abstract: | Model-based controllers based on incorrect estimates of the true plant behaviour can be expected to perform poorly. This work studies the effect of model plant mismatch on the closed loop behaviour and system performance for a certain class of MIMO systems. Performance is measured using a minimum variance index and a closely related user-specified criterion. We study the effect of model plant mismatch on the output variance and performance indices. Under mild assumptions, the performance of each output in a MIMO system can be analysed independently. Moreover, we propose an approach to distinguish the effect of model–plant mismatch from the effect of changes in disturbance characteristics on closed-loop performance. We define a sensitivity measure that relates system performance to model–plant mismatch, and use it to explore this sensitivity for three realistic types of parametric modelling errors. Next, we suggest a quantitative method that compares a system's actual output to its desired response in a transient setting. The performance of the transient response is demonstrably more sensitive to the model–plant mismatch than the steady state performance. The results are illustrated on industrial paper machine data. |
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| Keywords: | Performance monitoring MIMO systems Minimum variance control Sensitivity Paper machines |
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