Manual control cybernetics

State-of-the-art and current trends

Journal article (2017)

Authors

Max Mulder Control & Operations
David Abbink Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
E.R. Boer Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
P.M.T. Zaal San José State University,
Department
Control & Operations
Copyright: © 2017 Max Mulder, D.M. Pool, D.A. Abbink, E.R. Boer, P.M.T. Zaal, F.M. Drop, Kasper van der El, M.M. van Paassen
DOI: https://doi.org/10.1109/THMS.2017.2761342
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Published Date

2017

Language

English

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Department

Control & Operations

Abstract

Manual control cybernetics aims to understand and describe how humans control vehicles and devices using mathematical models of human control dynamics. This “cybernetic approach” enables objective and quantitative comparisons of human behavior, and allows a systematic optimization of human control interfaces and training associated with manual control. Current cybernetics theory is primarily based on technology and analysis methods formalized in the 1960s and has shown to be limited in its capability to capture the full breadth of human cognition and control. This paper reviews the current state-of-the-art in our knowledge of human manual control, points out the main fundamental limitations in cybernetics, and proposes a possible roadmap to advance the theory and its applications. Central in this roadmap will be a shift from the current linear time-invariant modeling approach that is only truly valid for human behavior under tightly controlled and stationary conditions, to methods that facilitate the analysis of adaptive, and possibly time-varying, human behavior in realistic control tasks. Examples of key current developments in the field of cybernetics—human use of preview, predictable discrete maneuvering, skill acquisition and training, time-varying human modeling, and neuromuscular system modeling—that contribute to this shift are presented in this paper. The new foundations for cybernetics that will emerge from these efforts will impact all domains that involve humans in manual and semiautomatic control.