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Memory pattern identification for feedback tracking control in human-machine systems

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journal contribution
posted on 03.10.2019 by Miguel Martinez-Garcia, Eve Zhang, Timothy Gordon
Objective: The aim of this paper was to identify the characteristics of memory patterns with respect to a visual input, perceived by the human operator during a manual control task, which consisted in following a moving target on a display with a cursor.
Background: Manual control tasks involve nondeclarative memory. The memory encodings of different motor skills have been referred to as procedural memories. The procedural memories have a pattern, which this paper sought to identify for the particular case of a onedimensional tracking task. Specifically, data recorded from human subjects controlling dynamical systems with different fractional order were investigated.
Method: A Finite Impulse Response (FIR) controller was fitted to the data, and pattern analysis was performed to the fitted parameters. Then, the FIR model was further reduced to a lower order controller; from the simplified model, the stability analysis of the human-machine system in closedloop was conducted.
Results: It is shown that the FIR model can be employed to identify and represent patterns in human procedural memories during manual control tasks. The obtained procedural memory pattern presents a time scale of about 650 ms before decay. Furthermore, the fitted controller is stable for systems with fractional order less or equal to 1.
Conclusion: For systems of different fractional order, the proposed control scheme – based on a FIR model – can effectively characterize the linear properties of manual control in humans.
Application: This research supports a biofidelic approach to human manual control modeling over feedback visual perceptions. Relevant applications of this research are: the development of shared-control systems, where a virtual human model assists the human during a control task, and human operator state monitoring.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Human Factors

Publisher

SAGE Publications

Version

AM (Accepted Manuscript)

Rights holder

© Human Factors and Ergonomics Society

Publisher statement

This paper was accepted for publication in the journal Human Factors and the definitive published version is available at https://doi.org/10.1177/0018720819881008. Users who receive access to an article through a repository are reminded that the article is protected by copyright and reuse is restricted to non-commercial and no derivative uses. Users may also download and save a local copy of an article accessed in an institutional repository for the user's personal reference.

Acceptance date

14/09/2019

Publication date

2019-10-24

Copyright date

2019

ISSN

0018-7208

eISSN

1547-8181

Language

en

Depositor

Dr Miguel Martinez Garcia

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