Shared control in aerial cyber-physical human systems

Abstract

This study considers the problem of control when two distinct decision makers, a human operator and an advanced automation working together, face severe uncer-tainties and anomalies. Under the rubric of Cyber-Physical Human Systems, we focus on shared control architectures (SCAs) that allow an advantageous combi-nation of human/automation abilities and provide a desired resilient performance. Humans and automation are likely to be interchangeable for routine tasks under normal conditions. However, under severe anomalies, the two entities provide complementary actions. It could be argued that human experts excel at cogni-tive tasks, such as anomaly recognition and estimation, while fast response with reduced latencies may be better accomplished by automation. For severe anoma-lies, we propose the use of a common metric called capacity for maneuver (CfM) that enables a smooth, bumpless transition when severe anomalies occur. It can be identified in control systems as the actuator’s proximity to its limits of satu-ration. Three different SCAs are presented, two of which use CfM by describing how human experts and automation can participate in a shared control action and recover gracefully from anomalous situations. Two of the SCAs are validated using human-in-the-loop experiments. The last SCA is exemplified theoretically, in which an analytical framework for the equations of motion of flexible quadrotor unmanned aerial vehicles is derived. A low-frequency adaptive controller together with a human pilot model is implemented using the developed model to prevent excessive oscillations due to flexible dynamics and to compensate uncertainties.