Parameter identification for an autonomous 11th order nonlinear model of a physiological process

A. Rundell, R. DeCarlo, P. Doerschuk, H. HogenEsch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper sets forth and illustrates some techniques for parameter identification (PId) of a nonlinear state model that approximates the dynamical behavior of the humoral immune response of a human to Haemophilus influenzae Type-b. The natural physiological time-separation of the primary, late follicular, and secondary immune responses of this biological process allows us to divide the PId problem into a sequence of smaller PId sub-problems. To reduce the dimension of the PId even further, coupling effects are minimized or eliminated by temporarily replacing variables and/or certain other functions of variables by approximate a priori known time functions called exogenous inputs. This sequence of low dimensional PId problems entails matching a set of one or two parameters at each step to a time-attribute pair defined as a maximum or minimum measured concentration level in a given time window. The identification sub-problem solution reduces to the inverse of an approximate local parameter-to-measurement map. The techniques presented herein are applicable to other nonlinear systems which exhibit similar time-sequenced properties.

Original languageEnglish (US)
Title of host publicationProceedings of the 1998 American Control Conference, ACC 1998
Pages3585-3589
Number of pages5
DOIs
StatePublished - Dec 1 1998
Externally publishedYes
Event1998 American Control Conference, ACC 1998 - Philadelphia, PA, United States
Duration: Jun 24 1998Jun 26 1998

Publication series

NameProceedings of the American Control Conference
Volume6
ISSN (Print)0743-1619

Other

Other1998 American Control Conference, ACC 1998
CountryUnited States
CityPhiladelphia, PA
Period6/24/986/26/98

Keywords

  • Biological process
  • Humoral immune response
  • Identification
  • Nonlinear model
  • Simulation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Rundell, A., DeCarlo, R., Doerschuk, P., & HogenEsch, H. (1998). Parameter identification for an autonomous 11th order nonlinear model of a physiological process. In Proceedings of the 1998 American Control Conference, ACC 1998 (pp. 3585-3589). [703280] (Proceedings of the American Control Conference; Vol. 6). https://doi.org/10.1109/ACC.1998.703280