Human Stability Analysis on Time-Delayed Teleoperation Tasks

In this paper, we present our first experimental results on the real-time stability analysis of the human operator performing on time-delayed teleoperation system. Due to the fact that human operator behavior is non linear, time varying and the complexity of the techniques to analyze in real-time this kind of systems, we used a discrete linearization of the model and determined for each sample if the system is stable or unstable. In this way, the stability analysis is based on the real-time identified model of the human operator and the Routh-Hurwitz stability criteria is applied to the model. The reason to use Routh-Hurwits instead of Jury criteria is due to the required amount of computational steps. Having determined if the system is stable or unstable in the sampling time, we are able to evaluate the human operator performance. In this way, the proportion of stable and unstable points obtained in the execution of a certain task, provides a performance indicator. The main result of this analysis indicates that human performance, measured as the proportion of stable / unstable points, is increased with repetitive executions of the task and independent of the magnitude of the delay in the visual feedback information.