Fundamental issues in manual control cybernetics

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Abstract

Manual control cybernetics aims to understand and describe how humans control vehicles and devices, such that more effective human-machine interfaces can be designed. Current cybernetics theory is primarily based on technology and analysis methods developed in the 1960s and has shown to be limited in its capability to capture the full breadth of human cognition and control. This paper summarizes some of the main fundamental limitations in cybernetics and provides a possible road-map to advance the theory and its applications. Central in this agenda will be a shift from the current linear time-invariant modeling approach, to the use of linear parameter-varying system models. Recent progress in identification methods of these latter models may allow us, for the first time, to mathematically model and identify time-varying, adaptive human control, opening up many opportunities to systematically optimize our human control interfaces and training. New foundations for cybernetics will impact all domains that involve humans in manual and semi-automatic control.