Human as an Actuator Dynamic Model Identification

Fuente: arXiv
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Hauptverfasser: Bonner, Harrison M., Kirchner, Matthew R.
Format: Preprint
Veröffentlicht: 2026
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author Bonner, Harrison M.
Kirchner, Matthew R.
author_facet Bonner, Harrison M.
Kirchner, Matthew R.
contents This paper presents a method for estimating parameters that form a general model for human pilot response for specific tasks. The human model is essential for the dynamic analysis of piloted vehicles. Data are generated on a simulator with multiple trials being incorporated to find the single model that best describes the data. The model is found entirely in the time domain by constructing a constrained optimization problem. This optimization problem implicitly represents the state of the underlying system, making it robust to natural variation in human responses. It is demonstrated by estimating the human response model for a position control task with a quadcopter drone.
format Preprint
id arxiv_https___arxiv_org_abs_2601_07956
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Human as an Actuator Dynamic Model Identification
Bonner, Harrison M.
Kirchner, Matthew R.
Systems and Control
Optimization and Control
This paper presents a method for estimating parameters that form a general model for human pilot response for specific tasks. The human model is essential for the dynamic analysis of piloted vehicles. Data are generated on a simulator with multiple trials being incorporated to find the single model that best describes the data. The model is found entirely in the time domain by constructing a constrained optimization problem. This optimization problem implicitly represents the state of the underlying system, making it robust to natural variation in human responses. It is demonstrated by estimating the human response model for a position control task with a quadcopter drone.
title Human as an Actuator Dynamic Model Identification
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2601.07956