Improving Manual Tracking of Systems With Oscillatory Dynamics

• Published in: IEEE transactions on human-machine systems Vol. 43; no. 1; pp. 46 - 52
• Main Authors: Potter, J. J., Singhose, W.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Chief executive officers; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Computer systems performance. Reliability; Cranes; Damping; Dynamical systems; Dynamics; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Human factors; Humans; Input shaping; Manual control; manual tracking; Manuals; Oscillations; Oscillators; Performance enhancement; Physics; Software; Solid mechanics; Structural and continuum mechanics; Studies; Tasks; Tracking; Transfer functions; vibration; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Input shaping; Performance evaluation; Tracking; Man machine system; Manual control; Frequency domain method; Tracking task; Dynamical system; vibration; Low frequency; Modeling; Frequency control; manual tracking; Task difficulty; Frequency characteristic; Active system; Oscillation; Vibration control; High frequency
• ISSN: 2168-2291; 2168-2305
• DOI: 10.1109/TSMCA.2012.2214031

This paper examines the manual control of systems with oscillatory dynamics. Tracking performance is improved by using input shaping to suppress command-induced oscillation. An operator study tested tracking behavior using controlled elements with both low-frequency (1.25 rad/s) and high-frequency (5 rad/s) oscillatory modes. After each experimental trial, measures of tracking performance and subjective task difficulty were recorded, and frequency-domain control characteristics were computed. Results showed that the high-frequency oscillatory mode did not greatly decrease the tracking performance from the nonoscillatory case; thus, input shaping did not produce a significant improvement in the tracking performance. However, input shaping did cause a decrease in the average subjective task difficulty and made the system closely resemble McRuer's "crossover model." For the low-frequency case, the addition of input shaping significantly improved the tracking performance and reduced the tracking difficulty. These results demonstrate that input shaping can greatly improve the continuous tracking ability of human-machine systems that have oscillatory modes.