Desarrollo de la estrategia iMO-NMPC: primeros pasos para su implementación en dispositivos industriales

  1. Zabaljauregi, Asier 1
  2. Alonso, Aimar 1
  3. Larrea, Mikel 1
  4. Irigoyen, Eloy 1
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Libro:
XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)
  1. Carlos Balaguer Bernaldo de Quirós (coord.)
  2. José Manuel Andújar Márquez (coord.)
  3. Ramon Costa Castelló (coord.)
  4. Carlos Ocampo Martínez (coord.)
  5. Jesús Fernández Lozano (coord.)
  6. Matilde Santos Peñas (coord.)
  7. José Enrique Simó Ten (coord.)
  8. Montserrat Gil Martínez (coord.)
  9. Jose Luis Calvo Rolle (coord.)
  10. Raúl Marín Prades (coord.)
  11. Eduardo Rocón de Lima (coord.)
  12. Elisabet Estévez Estévez (coord.)
  13. Pedro Jesús Cabrera Santana (coord.)
  14. David Muñoz de la Peña Sequedo (coord.)
  15. José Luis Guzmán Sánchez (coord.)
  16. José Luis Pitarch Pérez (coord.)
  17. Oscar Reinoso García (coord.)
  18. Oscar Déniz Suárez (coord.)
  19. Emilio Jiménez Macías (coord.)
  20. Vanesa Loureiro Vázquez (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-841-8

Año de publicación: 2022

Páginas: 248-254

Congreso: Jornadas de Automática (43. 2022. Logroño)

Tipo: Aportación congreso

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Resumen

This work presents the methodology used by the Intelligent Control Research Group (GICI) at UPV/EHU, for the development of intelligent control strategies and their further implementation in real time platforms. This methodology establishes the procedure for the validation of these strategies, not only from the point of view of simulation, in the form of scripts, but also by bringing these developments to different industrial hardware for their subsequent implementation in real time in the form of s-functions. The use case presented and currently being implemented is the iMONMPC strategy, which integrates under a predictive control scheme, evolutionary algorithms for optimisation and neural networks for system modelling. This methodology is developed using the MATLAB/Simulink® simulation platform. These developments can be validated on industrial hardware, for which the automatic code generation provided by this tool will be used.

Fuente de los datos: Dialnet