A Control Architecture for Human-Machine Interaction in the Presence of Unreliable Automation and Operator Cognitive Limitations

摘要

In this paper we present a control architecture for human-in-the-loop wide area search munitions to reduce operator errors in the presence of unreliable automation and operator cognitive limitations. An optimal input tracking controller with adaptive automation uncertainty compensation and real-time workload assessment is developed to improve the system performance. Specifically, a novel adaptive update law based on the sequential probability ratio test (SPR.T) is proposed to identify the automation uncertainty and a receding horizon-based switching controller is developed to improve the human-machine interaction (HMI) performance. Extensive simulations based on the experimental data involving 12 subjects demonstrate effectiveness of the presented controller.