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Related Experiment Videos

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR.

Sunil L Kukreja1, Robert E Kearney, Henrietta L Galiana

  • 1NASA Dryden Flight Research Center, Edwards, CA 93523-0273, USA. sunil.kukreja@nasa.gov

IEEE Transactions on Bio-Medical Engineering
|March 12, 2005
PubMed
Summary

This study introduces a new method for identifying and estimating parameters in switched systems, which have complex operational modes. The approach effectively models impulsive-smooth behaviors, improving analysis of nonlinear biosystems like the Vestibulo-Ocular Reflex (VOR).

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Area of Science:

  • Systems Engineering
  • Control Theory
  • Biomedical Engineering

Background:

  • Multimode or switched systems exhibit complex behaviors with discontinuities during operational mode transitions.
  • Current methods for identifying and parameterizing these systems are inadequate, often requiring data preprocessing.
  • The nonlinear dynamics and parameter estimation challenges in switched systems remain an unresolved problem.

Purpose of the Study:

  • To demonstrate the suitability of the Nonlinear Autoregressive Moving Average with eXogenous inputs (NARMAX) model for describing switched system dynamics.
  • To propose a Modified Extended Least Squares (MELS) algorithm for estimating coefficients in NARMAX models of switched systems.
  • To validate the proposed approach using simulated data and real-world data from the Vestibulo-Ocular Reflex (VOR).

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Main Methods:

  • Utilizing the NARMAX model structure to capture the impulsive-smooth transitions characteristic of switched systems.
  • Developing and applying a Modified Extended Least Squares (MELS) algorithm for parameter estimation.
  • Testing the methodology on simulated datasets and experimental Vestibulo-Ocular Reflex (VOR) data.

Main Results:

  • The NARMAX model structure effectively describes the impulsive-smooth behavior of switched systems.
  • The MELS algorithm successfully estimates model coefficients for switched systems.
  • The approach demonstrates practical applicability in analyzing the Vestibulo-Ocular Reflex (VOR) and other nonlinear biosystems.

Conclusions:

  • The NARMAX model and MELS algorithm provide a robust framework for identifying and parameterizing switched systems.
  • This method addresses limitations in current approaches, enabling better analysis of complex nonlinear biosystems.
  • The findings pave the way for improved understanding and modeling of biological systems with hard nonlinearities.