Improving performance and stability of MPC relevant identification methods

• MRI methods are a good option for identification if there is model structure mismatch.
• The predictor stability of the EMPEM is ensured through constraints.
• The disturbance model of the EMPEM is optimized over a prediction horizon.
• Statistical analysis shows that EMPEM is equal or better than the other methods.
• The EMPEM is more robust, mainly with small SNR and inaccurate time delay.

Model Predictive Control (MPC) Relevant Identification (MRI) methods are a good option for identification, if there is model structure mismatch. Herein a new MRI method, named Enhanced Multistep Prediction Error Method (EMPEM), is proposed. EMPEM combines the best characteristics of others MRI methods in a single algorithm. It was developed to identify either closed-loop or open-loop systems; its convergence and stability make it perform better than the other presented methods. To show the advantages of EMPEM, a comparison is made against two other methods (one MRI and one PEM). The statistical analysis indicates that in the cases studied, the performance and the robustness of the new method is equal or better than the other ones.