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The impact of static output nonlinearities on the control strategies that humans use in command-following tasks

Producción científica: Articlerevisión exhaustiva

Resumen

The results of a human-in-the-loop experiment are used to investigate the control strategies that humans use to interact with nonlinear dynamic systems. Two groups of human subjects interact with a dynamic system and perform a command-following task. The first group interacts with a linear time-invariant (LTI) dynamic system. The second group interacts with a Wiener system, which consists of the same LTI dynamics cascaded with a static output nonlinearity. Both groups exhibit improved performance over the trials, but the average of the linear group's performance is better on more than three-fourths of the trials. A new nonlinear subsystem identification algorithm is presented and used to identify the feedback and feedforward control strategies used by the subjects in both groups. The identification results for the linear group agree with prior studies suggesting that adaptive feedforward inversion is a primary control strategy used by humans for command-following tasks. The main results of this paper address an open question of whether a similar control strategy is used for nonlinear systems. The identification results for the nonlinear group suggest that those subjects also use adaptive feedforward inversion. However, the static output nonlinearity inhibits the human's ability to approximate the inverse.

Idioma originalEnglish
Páginas (desde-hasta)2964-2986
Número de páginas23
PublicaciónJournal of the Franklin Institute
Volumen358
N.º6
DOI
EstadoPublished - abr 2021

Nota bibliográfica

Publisher Copyright:
© 2021 The Franklin Institute

Financiación

This work is supported in part by the National Science Foundation (award number: OIA-1849213 , CMMI-1405257 )

FinanciadoresNúmero del financiador
National Science Foundation Arctic Social Science Program1849213, OIA-1849213, CMMI-1405257

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Signal Processing
    • Computer Networks and Communications
    • Applied Mathematics

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