Identification of a nonlinear dynamic biological model using the dominant parameter selection method

Ioslovish, I., Ramirez Sosa Moran, M.I. and Gutman Per-O 2010. Identification of a nonlinear dynamic biological model using the dominant parameter selection method. Journal of the Franklin Institute. 347 (6), pp. 1001-1014. https://doi.org/10.1016/j.jfranklin.2009.11.007

Title Identification of a nonlinear dynamic biological model using the dominant parameter selection method
AuthorsIoslovish, I., Ramirez Sosa Moran, M.I. and Gutman Per-O
Abstract

The identification of nonlinear models sometimes encounters problems because of the limited amount of available measurements in combination with a large number of uncertain model parameters to be identified. E.g., the determination of the chemical composition of a lettuce crop is a rather expensive procedure; thus the number of experimental measurements is limited. As a result, the number of parameters of the dynamic model that can be successively identified is also limited, and the subset of the parameters to be identified must be chosen in a reasonable way.

Parameter estimation for an extended nonlinear three-state model for lettuce growth in greenhouses is presented in this paper. The varying structural nitrogen concentration and water contents are the new elements included in the model. The dominant parameter selection (DPS) method was used to select a suitable set of identifiable parameters. The resulting calibrated model predicts quite well the experimental data which also include observations with severe nitrogen stress.

KeywordsNonlinear identification; Lettuce growth; Nicolet model
JournalJournal of the Franklin Institute
Journal citation347 (6), pp. 1001-1014
ISSN0016-0032
Year2010
PublisherElsevier
Digital Object Identifier (DOI)https://doi.org/10.1016/j.jfranklin.2009.11.007
Publication dates
Published22 Dec 2009
PublishedAug 2010
FunderCouncil of Europe

Related outputs

An experimental validation of NICOLET B3 mathematical model for lettuce growth in the southeast region of Coahuila México by dynamic simulation
Juárez-Maldonado, A., De-Alba-Romenus, K., Ramirez Sosa Moran, M.I., Benavides-Mendoza, A. and Robledo-Torres, V. 2010. An experimental validation of NICOLET B3 mathematical model for lettuce growth in the southeast region of Coahuila México by dynamic simulation . 2010 7th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2010). Tuxtla Gutiérrez, Chiapas, México. September 8-10, 2010 08 Sep 2010 IEEE . https://doi.org/10.1109/ICEEE.2010.5608663

A Single-Frame Super-Resolution Innovative Approach
Ramirez Sosa Moran, M.I., Torres-Méndez, L.A. and Castelán, M. 2007. A Single-Frame Super-Resolution Innovative Approach. in: MICAI 2007: Advances in Artificial Intelligence Springer. pp. 640-649

Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal
Ramirez Sosa Moran, M.I., Castelán, M., Almazán-Delfín, A.J. and Torres-Méndez, L.A. 2007. Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal. in: MICAI 2007: Advances in Artificial Intelligence Springer. pp. 758-768

Nonlinear Dynamic Lettuce Growth Model: Parameter Selection and Estimation for N-Limited Experiments
Ioslovish, I., Ramirez Sosa Moran, M.I. and Gutman Per-O 2005. Nonlinear Dynamic Lettuce Growth Model: Parameter Selection and Estimation for N-Limited Experiments . Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. Seville, Spain, December 12-15, 2005 12 Dec 2005 IEEE . https://doi.org/10.1109/CDC.2005.1583043

Robust stability of a diamond of complex multivariate polynomials
Ramirez Sosa Moran, M.I. 2001. Robust stability of a diamond of complex multivariate polynomials. American Control Conference, 2001. Proceedings of the 2001. Arlington, VA 25 Jun 2001 IEEE . https://doi.org/10.1109/ACC.2001.945723

Robust Stability of Multivariate Polynomials, Part 3: Frequency Domain Approach
Kharitonov, V.L., Ramirez Sosa Moran, M.I. and Torres-Munoz, J.A. 2000. Robust Stability of Multivariate Polynomials, Part 3: Frequency Domain Approach. Multidimensional Systems and Signal Processing. 11 (3), pp. 213-231. https://doi.org/10.1023/A:1008434513790

On multivariate zero exclusion principle: application to stability radius
Ramirez Sosa Moran, M.I., Torres-Munoz, J.A. and Kharitonov, V.L. 1999. On multivariate zero exclusion principle: application to stability radius . Decision and Control. Phoenix, AZ 07 Dec 1999 IEEE . https://doi.org/10.1109/CDC.1999.833256

Robust Stability of Multivariate Polynomials, Part 2: Polytopic Coefficient Variations
Kharitonov, V.L., Torres-Munoz, J.A. and Ramirez Sosa Moran, M.I. 1999. Robust Stability of Multivariate Polynomials, Part 2: Polytopic Coefficient Variations. Multidimensional Systems and Signal Processing. 10 (1), pp. 21-32. https://doi.org/10.1023/A:1008437801340

Robust stability of a diamond of multivariate polynomials
Ramirez Sosa Moran, M.I. and Kharitonov, V.L. 1998. Robust stability of a diamond of multivariate polynomials. American Control Conference. Philadelphia, PA 21 Jun 1998 IEEE . https://doi.org/10.1109/ACC.1998.703273

Stability and robust stability of multivariate polynomials
Kharitonov, V.L., Torres-Munoz, J.A. and Ramirez Sosa Moran, M.I. 1997. Stability and robust stability of multivariate polynomials. Decision and Control, 1997., Proceedings of the 36th IEEE Conference on . San Diego, CA 10 Dec 1997 IEEE . https://doi.org/10.1109/CDC.1997.652346

Permalink - https://westminsterresearch.westminster.ac.uk/item/9w387/-identification-of-a-nonlinear-dynamic-biological-model-using-the-dominant-parameter-selection-method


Share this

Usage statistics

108 total views
0 total downloads
These values cover views and downloads from WestminsterResearch and are for the period from September 2nd 2018, when this repository was created.