A variably tuned multiple model predictive controller based on minimal process knowledge
- 1 January 2001
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 5, 3490-3495 vol.5
- https://doi.org/10.1109/acc.2001.946173
Abstract
A multiple model predictive controller is designed using minimal plant knowledge based on the ranges on gains, dominant time constants and time delays. The algorithm uses a weighted multiple model bank of first order plus deadtime models as the prediction model for a constrained model predictive controller. A variable tuning strategy is implemented to improve controller performance. The simulated process I'S the isothermal Van de Vusse reaction in a continuously stirred tank reactor (CSTR); this system exhibits input multiplicities, making it a challenging control problem.Keywords
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