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Studying the Use of ANN to Estimate State-Space Variables for MIMO Systems in a NMPC Strategy

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17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) (SOCO 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 531))

Abstract

The integration of new technologies in advanced control systems continues to be a current challenge today, as control devices gain in performance and new alternatives to existing techniques are offered. This is based on the fact that the techniques from Intelligent Computing allow the development of efficient and robust control systems, without the need to fully understand the dynamics of the plant. On the other hand, the use of predictive control is a reality within the world of the process industry. It is widely used in the industrial environment due to its simplicity and robustness. The objective of this work is to study and assess the possibility of using neural models to reproduce the dynamics of complex multivariable systems, together with their applicability in control strategies that use optimization processes to generate the appropriate control actions and considering operational constraints, as is the case of the nonlinear MPC. In this work, the results obtained along the this study will be presented, where it is analyzed how to include said neuronal model in a previously established non-linear MPC strategy.

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Acknowledgments

This work comes under the framework of the projects PID2020-120087GB-C22 and PID2020-120087GB-C21 granted by the Ministry of Science and Innovation of the Government of Spain. (AEI/http://dx.doi.org/10.13039/501100011033).

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Authors and Affiliations

  1. University of the Basque Country (UPV/EHU), Leioa, Spain

    Aimar Alonso, Asier Zabaljauregi, Mikel Larrea & Eloy Irigoyen

  2. Universitat Politècnica de València (UPV), Valencia, Spain

    Javier Sanchís

Authors
  1. Aimar Alonso
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  2. Asier Zabaljauregi
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  3. Mikel Larrea
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  4. Eloy Irigoyen
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  5. Javier Sanchís
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Corresponding author

Correspondence to Eloy Irigoyen .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of León, León, Spain

    Hilde Pérez García

  3. Mechanical Engineering Department, University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martinez-de-Pison

  4. Inteligencia Artificial, University of Oviedo, A Coruña, La Coruña, Spain

    José Ramón Villar Flecha

  5. Data Science and Big Data Lab, Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso Lora

  6. University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  8. School of engineering, Pablo Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Emilio S. Corchado Rodriguez

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Alonso, A., Zabaljauregi, A., Larrea, M., Irigoyen, E., Sanchís, J. (2023). Studying the Use of ANN to Estimate State-Space Variables for MIMO Systems in a NMPC Strategy. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_45

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