Objective model selection for identifying the human feedforward response in manual control

Frank M. Drop, Daan M. Pool, Marinus M. Van Paassen, Max Mulder, Heinrich H. Bülthoff

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: “false-positive” feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

Original languageEnglish
Pages (from-to)2-15
Number of pages14
JournalIEEE Transactions on Cybernetics
Issue number1
Publication statusPublished - 2018 Jan

Bibliographical note

Publisher Copyright:
© 2016 IEEE.


  • Human control models
  • Index Terms—Feedforward control
  • Manual control
  • Parameter estimation
  • System identification

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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