Identifying Time-Varying pilot's responses

A regularized recursive Least-Squares algorithm

Mario Olivari, Joost Venrooij, Frank M. Nieuwenhuizen, Lorenzo Pollini, Heinrich Bulthoff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Methods for identifying pilot's responses commonly assume time-invariant dynamics. However, humans are likely to vary their responses during realistic control scenarios. In this work an identification method is developed for estimating time-varying responses to visual and force feedback during a compensatory tracking task. The method describes pilot's responses with finite impulse response filters and use a Regularized Recursive Least Squares (RegRLS) algorithm to simultaneously estimate filter coefficients. The method was validated in a Monte-Carlo simulation study with different levels of remnant noise. With low levels of remnant noise, estimates were accurate and tracked the time-varying behaviour of the simulated responses. On the other hand, estimates showed high variability in case of large remnant noise. However, parameters of the RegRLS could be further optimized to improve robustness to large remnant noise. Taken together, these findings suggest that the novel RegRLS algorithm could be used to estimate time-varying pilot's responses in real human-in-the-loop experiments.

Original languageEnglish
Title of host publicationAIAA Modeling and Simulation Technologies Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624103872
Publication statusPublished - 2016
EventAIAA Modeling and Simulation Technologies Conference, 2016 - San Diego, United States
Duration: 2016 Jan 42016 Jan 8

Other

OtherAIAA Modeling and Simulation Technologies Conference, 2016
CountryUnited States
CitySan Diego
Period16/1/416/1/8

Fingerprint

Least Square Algorithm
Recursive Algorithm
Time-varying
FIR filters
Feedback
Estimate
Filter
Force Feedback
Experiments
Impulse Response
Least Squares
Monte Carlo Simulation
Likely
Simulation Study
Vary
Robustness
Scenarios
Invariant
Coefficient
Experiment

ASJC Scopus subject areas

  • Aerospace Engineering
  • Modelling and Simulation

Cite this

Olivari, M., Venrooij, J., Nieuwenhuizen, F. M., Pollini, L., & Bulthoff, H. (2016). Identifying Time-Varying pilot's responses: A regularized recursive Least-Squares algorithm. In AIAA Modeling and Simulation Technologies Conference American Institute of Aeronautics and Astronautics Inc, AIAA.

Identifying Time-Varying pilot's responses : A regularized recursive Least-Squares algorithm. / Olivari, Mario; Venrooij, Joost; Nieuwenhuizen, Frank M.; Pollini, Lorenzo; Bulthoff, Heinrich.

AIAA Modeling and Simulation Technologies Conference. American Institute of Aeronautics and Astronautics Inc, AIAA, 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Olivari, M, Venrooij, J, Nieuwenhuizen, FM, Pollini, L & Bulthoff, H 2016, Identifying Time-Varying pilot's responses: A regularized recursive Least-Squares algorithm. in AIAA Modeling and Simulation Technologies Conference. American Institute of Aeronautics and Astronautics Inc, AIAA, AIAA Modeling and Simulation Technologies Conference, 2016, San Diego, United States, 16/1/4.
Olivari M, Venrooij J, Nieuwenhuizen FM, Pollini L, Bulthoff H. Identifying Time-Varying pilot's responses: A regularized recursive Least-Squares algorithm. In AIAA Modeling and Simulation Technologies Conference. American Institute of Aeronautics and Astronautics Inc, AIAA. 2016
Olivari, Mario ; Venrooij, Joost ; Nieuwenhuizen, Frank M. ; Pollini, Lorenzo ; Bulthoff, Heinrich. / Identifying Time-Varying pilot's responses : A regularized recursive Least-Squares algorithm. AIAA Modeling and Simulation Technologies Conference. American Institute of Aeronautics and Astronautics Inc, AIAA, 2016.
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