Human as an Actuator Dynamic Model Identification

TL;DR

This paper introduces a time-domain optimization method to identify a general human response model for piloted vehicles, demonstrated on a quadcopter position control task.

Contribution

It develops a robust, time-domain constrained optimization approach for modeling human responses, applicable to various piloted vehicle systems.

Findings

Effective human response model estimation from simulator data

Robustness to natural human response variations

Successful application to quadcopter control task

Abstract

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.