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Nonlinear Parametric Model Identification with Genetic Algorithms. Application to a Thermal Process

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Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence (IWANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2084))

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Abstract

One of the first steps taken in any technological area is building a mathematical model. In fact, in the case of process control, modelling is a crucial aspect that influences quality control. Building a nonlinear model is a traditional problem. This paper illustrates how to built an accurate nonlinear model combining first principle modelling and a parametric identification, using Genetic Algorithms. All the experiments presented in this paper are designed for a thermal process.

This work has been partially financed by European FEDER funds, project 1FD97- 0974-C02-02

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References

  1. F. X. Blasco. Model based predictive control using heuristic optimization techniques. Application to non-linear and multivariables proceses. PhD thesis, Universidad Politécnica de Valencia, Valencia, 1999 (In Spanish).

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  5. Numerical Algorithms Group NAG. NAG Fortran Library. Introductory guide. Mark 18. Technical report, 1997.

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  6. M. Zamora. A study of the thermodynamic systems. Universidad de Sevilla, 1998 (In Spanish).

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Author information

Authors and Affiliations

  1. Predictive Control and Heuristic Optimization Group Department of Systems Engineering and Control, Universidad Politecnica de Valencia, Spain

    X. Blasco, J. M. Herrero, M. Martínez & J. Senent

Authors
  1. X. Blasco
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  2. J. M. Herrero
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  3. M. Martínez
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  4. J. Senent
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Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial Sanda del Rey, Universidad Nacional de Educación a Distancia, s/n., Madrid, 28040, Spain

    José Mira

  2. Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada, Campus Fuentenueva, 18071, Granada, Spain

    Alberto Prieto

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© 2001 Springer-Verlag Berlin Heidelberg

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Cite this paper

Blasco, X., Herrero, J.M., Martínez, M., Senent, J. (2001). Nonlinear Parametric Model Identification with Genetic Algorithms. Application to a Thermal Process. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_55

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  • DOI: https://doi.org/10.1007/3-540-45720-8_55

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42235-8

  • Online ISBN: 978-3-540-45720-6

  • eBook Packages: Springer Book Archive

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