Characteristics that make dynamic systems difficult for a human to control

S. Alireza Seyyed Mousavi; Xingye Zhang; T. M. Seigler; Jesse B. Hoagg

doi:10.1109/ACC.2016.7525613

Characteristics that make dynamic systems difficult for a human to control

S. Alireza Seyyed Mousavi, Xingye Zhang, T. M. Seigler, Jesse B. Hoagg

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

We present results from an experiment in which 55 human subjects each interact with a dynamic system 40 times over a one-week period. The subjects are divided into 5 groups of 11 subjects. Each group interacts with a different system. We use the experimental results to determine characteristics (e.g., system zeros, relative degree, phase lag) that can make systems difficult for a human to control. We use subsystem identification to model the control strategies (feedback and feedforward) that each subject uses during their first and last trials. For each group, the average identified feedforward controller on the last trial approximates the inverse dynamics of the system with which the subjects in that group interacted.

Original language	English
Title of host publication	2016 American Control Conference, ACC 2016
Pages	4391-4396
Number of pages	6
ISBN (Electronic)	9781467386821
DOIs	https://doi.org/10.1109/ACC.2016.7525613
State	Published - Jul 28 2016
Event	2016 American Control Conference, ACC 2016 - Boston, United States Duration: Jul 6 2016 → Jul 8 2016

Publication series

Name	Proceedings of the American Control Conference
Volume	2016-July
ISSN (Print)	0743-1619

Conference

Conference	2016 American Control Conference, ACC 2016
Country/Territory	United States
City	Boston
Period	7/6/16 → 7/8/16

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2016.7525613

Cite this

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title = "Characteristics that make dynamic systems difficult for a human to control",

abstract = "We present results from an experiment in which 55 human subjects each interact with a dynamic system 40 times over a one-week period. The subjects are divided into 5 groups of 11 subjects. Each group interacts with a different system. We use the experimental results to determine characteristics (e.g., system zeros, relative degree, phase lag) that can make systems difficult for a human to control. We use subsystem identification to model the control strategies (feedback and feedforward) that each subject uses during their first and last trials. For each group, the average identified feedforward controller on the last trial approximates the inverse dynamics of the system with which the subjects in that group interacted.",

author = "Mousavi, {S. Alireza Seyyed} and Xingye Zhang and Seigler, {T. M.} and Hoagg, {Jesse B.}",

note = "Publisher Copyright: {\textcopyright} 2016 American Automatic Control Council (AACC). Copyright: Copyright 2016 Elsevier B.V., All rights reserved.; 2016 American Control Conference, ACC 2016 ; Conference date: 06-07-2016 Through 08-07-2016",

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doi = "10.1109/ACC.2016.7525613",

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Mousavi, SAS, Zhang, X, Seigler, TM & Hoagg, JB 2016, Characteristics that make dynamic systems difficult for a human to control. in 2016 American Control Conference, ACC 2016., 7525613, Proceedings of the American Control Conference, vol. 2016-July, pp. 4391-4396, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7525613

Characteristics that make dynamic systems difficult for a human to control. / Mousavi, S. Alireza Seyyed; Zhang, Xingye; Seigler, T. M. et al.
2016 American Control Conference, ACC 2016. 2016. p. 4391-4396 7525613 (Proceedings of the American Control Conference; Vol. 2016-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - We present results from an experiment in which 55 human subjects each interact with a dynamic system 40 times over a one-week period. The subjects are divided into 5 groups of 11 subjects. Each group interacts with a different system. We use the experimental results to determine characteristics (e.g., system zeros, relative degree, phase lag) that can make systems difficult for a human to control. We use subsystem identification to model the control strategies (feedback and feedforward) that each subject uses during their first and last trials. For each group, the average identified feedforward controller on the last trial approximates the inverse dynamics of the system with which the subjects in that group interacted.

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Characteristics that make dynamic systems difficult for a human to control

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