Improving performance and stability of MPC relevant identification methods

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Date
2014
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Abstract
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. © 2013 Elsevier Ltd.
  1. Identification for control
  2. Model predictive control
  3. MPC relevant identification
  4. Multivariable identification
  5. Process identification
  6. Error analysis
  7. Model predictive control
  8. Convergence and stability
  9. Identification for control
  10. Identification method
  11. Improving performance
  12. Multi-step prediction
  13. Multivariable identifications
  14. Open loop systems
  15. Process identification
  16. Predictive control systems
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889575020&doi=10.1016%2fj.conengprac.2013.09.007&partnerID=40&md5=d9cf8dc730edbb597147394f02ec8511
https://repositorio.maua.br/handle/MAUA/1248
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