A subsystem identification technique for modeling control strategies used by humans

Xingye Zhang, Shaoqian Wang, T. M. Seigler, Jesse B. Hoagg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

This paper presents evidence in support of the internal model hypothesis of neuroscience. Specifically, we present results from a study that includes 10 human subjects and is designed to explore the internal model hypothesis. A new system identification method is presented for composite systems that include multiple unknown subsystems whose input and output signals may be inaccessible (i.e., unmeasurable). We use this subsystem identification method to model the control strategies that humans employ. In particular, we identify the feedback and feedforward controllers of the subjects in the experiment. The identified controllers suggest that the subjects learned to use inverse plant dynamics in feedforward.

Original languageEnglish
Title of host publication2014 American Control Conference, ACC 2014
Pages2827-2832
Number of pages6
DOIs
StatePublished - 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

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

Conference

Conference2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR
Period6/4/146/6/14

Keywords

  • Behavioral systems
  • Biologically-inspired methods
  • Identification

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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