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One of the challenges that still needs to be overcome in order to improve the performance of the model predictive control (MPC) is its maintenance. Re-identification of the process is one of the best options available to update the internal model of the MPC, in order to increase the production and improve efficiency. However, re-identification is costly Researchers have proposed two different methods able to detect plant mismatch through partial correlation analysis. Using these techniques, instead of re-identifying all the sub-models in the process, only a few inputs with significant mismatch would have to be perturbed and only the degraded portion of the model would be updated. Nevertheless, there isn’t enough information and analysis about the influence of the choice of the structures for identification (as FIR, ARX, ARMAX and OE) on partial correlation results. This paper demonstrates that the Carlsson method is a particular solution of the Badwe et al. method, when the models used on the identification process are FIR structures. Moreover, some other types of structures will were analyzed in order to check if they are suitable for the partial correlation procedure to detect plant mismatches. |
