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Meeting	ACGS Committee Meeting 127 - San Diego, CA - November 2021
Agenda Location	7 SUBCOMMITTEE C – AVIONICS AND SYSTEM INTEGRATION 7.3 A Theoretical Framework Unifying Handling Qualities, Workload, Stability, and Control
Title	A Theoretical Framework Unifying Handling Qualities, Workload, Stability, and Control
Presenter	Ed Bachelder
Affiliation	San Jose State University
Available Downloads*	presentation paper
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Abstract	The concepts and principles developed in this work offer a novel and integrative approach for exploring fundamental issues surrounding pilot performance, handling qualities (HQs), and workload. Basic laws of sensory perception are extended to multi-input sensing, showing that multiple sensory inputs add logarithmically. One of the objectives of this paper is to present evidence for the theory that an operator’s behavior during a manual tracking task is largely the result of two factors: 1) Pursuing a condition that is conducive to accessing phase margin (PM); and 2) Bounding tracking error. The two are highly coupled, and both drive performance and workload. PM is contained in the state information the operator can sense (i.e., tracking error, control activity), but in this raw form the relationship is often non-linear. It is well-established that human operators of dynamic systems prefer to control linear elements. Through a combination of state transformation (using skill-based perception) and appropriate compensation, phase margin (PM) is linearized and made accessible for supporting loop control. It is also shown that this behavior associated with PM linearization serves to reduce workload. Two contrasting sets of experimental data were used to examine pilot response, indicating that pilot compensation is effected via both frequency modulation (lead-lag) and temporal modulation (pure time delay). HQ sensing is treated as multi-input perception, where time delay and the lead-lag ratio are the stimuli for compensation sensing, and tracking error is the stimulus for performance sensing. A HQ metric arising from the logarithmic addition of these two sensations is shown to yield promising results. A cost function representing pilot behavioral objectives is developed that serves to modulate the following four items: 1) Tracking error; 2) Workload; 3) Linearity between workload and PM; and 4) Setting a reference PM. The pilot cost function was implemented in an optimal pilot which produced pilot time delay and pilot compensation estimates that closely matched the actual pilot data.