The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems

Xingye Zhang, Shaoqian Wang, Jesse B. Hoagg, T. Michael Seigler

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

Original languageEnglish
Article number7835227
Pages (from-to)543-555
Number of pages13
JournalIEEE Transactions on Cybernetics
Issue number2
StatePublished - Feb 2018

Bibliographical note

Funding Information:
Manuscript received September 22, 2016; accepted December 4, 2016. Date of publication January 26, 2017; date of current version January 15, 2018. This work was supported in part by the National Science Foundation under Award CMMI-1405257, and in part by the Kentucky Science and Engineering Foundation under Award KSEF-148-502-12-288. This paper was recommended by Associate Editor A. Behal. (Corresponding author: Jesse B. Hoagg.) The authors are with the Department of Mechanical Engineering, University of Kentucky, Lexington, KY 40506 USA (e-mail:

Publisher Copyright:
© 2017 IEEE.


  • Human motor control
  • internal model
  • subsystem identification (SSID)

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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