Contributions of feedforward and feedback control in a manual trajectory-tracking task. Issue 34 (2019)

• Record Type: Journal Article
• Authors: Yamagami, Momona; Howell, Darrin; Roth, Eatai; Burden, Samuel A.
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 34(2019)
• Page Start: 61
• Page End: 66
• Publication Date: 2019
• Subjects: internal inverse model -- sensorimotor learning -- system identification; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2019.01.025
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In joint human-cyber-physical systems, the human operator may rely on a combination of reactive (feedback) and predictive (feedforward) control. This paper proposes an experimental and analytical approach to simultaneously identify the human feedback and feedforward controllers in the context of human-cyber-physical systems (HCPS). In our experiments, participants play a 1DOF reference-tracking video game, tasked to guide a cursor to follow a pseudo-random trajectory. For such tasks, the model inversion hypothesis suggests that the human operator would implement as a feedforward controller the inverse of the cyber-physical-system dynamics. Our results indicate that at lower frequencies (≤ 0.15 Hz), individuals capably invert the system dynamics to implement a feedforward controller, but at higher frequencies, the magnitudes of the estimated feedforward transformation are approximately half those of the exact model inverse. This suggests that a frequency limit at which individuals are unable to follow the system dynamics, and thus, the model inversion prediction is only applicable at lower frequencies.