Parametric Mismatch Detection and Isolation in Model Predictive Control System1

Predictor that is built from the plant model, plays an important role in model predictive control system. The predictor should be updated timely to maintain certain calculation accuracy and performance optimality. In order to avoid unnecessary interruptions to production, however, updating should only be done when serious mismatch between the process and model appears. A novel method based on subspace approach is proposed to detect the mismatches using closed-loop operation data. The channels with mismatches in multi input multi output system are isolated. And some combinations of the mismatched parameters that have physical significance can be detected. These results provide useful information for the maintenance of model predictive control system. Simulations on a distillation process demonstrate the efficacy of the methodology.