Browsing by Author "Eraslan, Emre"

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Open Access
Safe shared control between pilots and autopilots in the face of anomalies
(Wiley, 2023-06-09) Eraslan, Emre; Yıldız, Yıldıray; Annaswamy, Anuradha M.
As societal drivers of sustainability, efficiency and quality of life become more urgent and intensive, analysis and synthesis of safety critical systems in the face of anomalies become extremely important. In applications such as fully autonomous ground or air transportation, in electrical grids, and healthcare, often there are two decision-makers, one of which is automation, and the other is a human expert. While there have been several studies undertaken to understand the role of automation, and that of human experts, how the two decision-makers can carry out a shared control in a safety-critical system in the face of anomalies has not been investigated in depth. Our focus in this chapter is on two different shared control architectures for a cyber–physical–human system (CPHS), where the decision-making of the human expert is judiciously combined with that of an advanced automation with cyber components of sensing, computation, communication, and actuation. These architectures are evaluated in the context of flight control problems when severe anomalies are present. It is argued that for a successful synthesis of CPHS a granularity assignment of task allocation and timeline has to be carried out which enables the coordination between human and automation, the specific tasks that they carry out, and the timeline associated with these tasks, all in the context of an anomaly. Models of the physical system, the automation, and the pilot using two different shared control architectures are discussed. Validation of these architectures with a simulation study with human-in-the-loop of flight control problems is reported, demonstrating the design of successful CPHS in the presence of severe anomalies.
Open Access
Shared control between pilots and autopilots: an illustration of a cyberphysical human system
(IEEE, 2020) Eraslan, Emre; Yıldız, Yıldıray; Annaswamy, A. M.
This article considers the problem of control when two distinct decision makers, a human operator and an advanced automation working together, face severe uncertainties and anomalies. We focus on shared control architectures (SCAs) that allow an advantageous combination of their 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 cognitive tasks, such as anomaly recognition and estimation, while fast response with reduced latencies may be better accomplished by automation. This then suggests that architectures that combine their action must be explored. One of the major challenges with two decision makers in the loop is bumpy transfer when control responsibility switches between them. We propose the use of a common metric that enables a smooth, bumpless transition when severe anomalies occur. This common metric is termed capacity for maneuver (CfM), which is a concept rooted in human behavior and can be identified in control systems as the actuator’s proximity to its limits of saturation. Two different SCAs are presented, both of which use CfM, and describe how human experts and automation can participate in a shared control action and recover gracefully from anomalous situations. Both of the SCAs are validated using human-in-the-loop experiments. The first architecture consists of a traded control action, where the human expert assumes control from automation when the CfM drops below a certain threshold and ensures a bumpless transfer. The second architecture includes a supervisory control action, where the human expert determines the tradeoff between the CfM and the corresponding degradation in command following and transmits suitable parameters to the automation when an anomaly occurs. The experimental results show that, in the context of flight control, these SCAs result in a bumpless, resilient performance.
Open Access
Shared control in aerial cyber-physical human systems
(2021-06) Eraslan, Emre
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.