Conference paper
Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Department of Chemical and Biochemical Engineering, Technical University of Denmark3
CAPEC-PROCESS, Department of Chemical and Biochemical Engineering, Technical University of Denmark4
A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays.
It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model is to be applied. The suitability of the proposed prediction error-method for predictive control is demonstrated for dual composition control of a simulated binary distillation column.
Language: | English |
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Publisher: | IEEE |
Year: | 2007 |
Pages: | 4752-4758 |
Proceedings: | European Control Conference 2007European Control Conference |
ISBN: | 3952417386 and 9783952417386 |
Types: | Conference paper |
DOI: | 10.23919/ECC.2007.7068799 |
ORCIDs: | Jørgensen, John Bagterp and Jørgensen, Sten Bay |