Dual-axis manual control

Abstract

Vehicle control tasks require simultaneous control of multiple degrees-of-freedom. Most multi-axis human-control modeling is limited to the modeling of multiple fully independent single axes. This paper contributes to the understanding of multi-axis control behavior and draws a more realistic and complete picture of dual-axis manual control. A human-in-the-loop experiment was performed to study four distinctive phenomena that can occur in multi-axis control: performance degradation, axis asymmetry, crossfeed, and intermittency. In a simulator, three conditions were tested in the presence and absence of physical motion: the full dual-axis control task, single-axis roll task, and single-axis pitch task. Controlled element dynamics, stick dynamics, and forcing functions were equal in all cases. Results show that performance is worse in dual-axis tasks. Performance in roll axis is consistently worse than pitch, thereby proving axis asymmetry. Physical motion improves the performance and stability of the system. The application of independent forcing function signals in both controlled axes resulted in the detection of crossfeed in dual-axis tasks from spectral analysis. Using a novel extended Fourier coefficient method, the identified crossfeed dynamics can explain up to 20% of the measured control inputs and improves modeling accuracy by up to 5%. Dual-axis control behavior is less accurately modeled with linear time-invariant models and is more intermittent.