Design of H∞ command and control loops for unmanned aerial vehicles using static output-feedback

2007 ◽  
Author(s):  
J. Gadewadikar ◽  
F. Lewis ◽  
K. Subbarao ◽  
Ben M. Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Output Feedback ◽  
Command And Control ◽  
Static Output Feedback ◽  
Control Loops ◽  
Aerial Vehicles ◽  
And Control ◽  
Static Output

scholarly journals Design and Analysis of Collaborative Unmanned Surface-Aerial Vehicle Cruise Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Man Zhu ◽  
Yuan-Qiao Wen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Command And Control ◽  
Collaborative Model ◽  
Weighting Method ◽  
Unmanned Surface Vehicle ◽  
Control Networks ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
And Control

With the increasing application of unmanned surface vehicle-unmanned aerial vehicles (USV-UAVs) in maritime supervision, research on their deployment and control is becoming vitally important. We investigate the application of USV-UAVs for synergistic cruising and evaluate the effectiveness of the proposed collaborative model. First, we build a collaborative model consisting of the cruise vehicles and communication, detection, and command-and-control networks for the USV-UAV. Second, based on an analysis of the problems faced by collaborative USV-UAV systems, we establish a model to evaluate the effectiveness of such synergistic cruises. Third, we propose a weighting method for each evaluation factor. Finally, a model consisting of one UAV and four USVs is employed to validate our synergistic cruise model.

Using Heart Rate Variability to Assess Operator Mental Workload in a Command and Control Simulation of Multiple Unmanned Aerial Vehicles

2016 ◽  
Vol 60 (1) ◽  
pp. 1125-1129 ◽  
Author(s):  
Phillip Jasper ◽  
Ciara Sibley ◽  
Joseph Coyne
Keyword(s):  
Heart Rate ◽  
Unmanned Aerial Vehicles ◽  
Mental Workload ◽  
Command And Control ◽  
Control Simulation ◽  
Aerial Vehicles ◽  
Single Vehicle ◽  
Multiple Unmanned Aerial Vehicles ◽  
And Control ◽  
Operator Workload

Unmanned systems will play an increased role in the future beyond military application including but not limited to: search and rescue, border patrol, homeland security, and natural disaster relief operations. Current models of unmanned system operations, such as those used for unmanned aerial vehicles, require multiple operators to control a single vehicle. This multioperator-single vehicle ratio will soon shift to a multioperator-multivehicle model as the number of unmanned systems increase and work in unison to complete a mission. The purpose of this study was to determine the utility of a physiological measure i.e. heart rate variability (HRV), to assess operator workload in a single operator-multivehicle command and control simulation. An internally developed command and control simulator is described and observed effects of mental workload on HRV are reported. Results suggest that HRV can be used to assess operator workload during a command and control simulation of multiple unmanned aerial vehicles.

Operator Workload Reduced in Unmanned Aerial Vehicles: Making Command and Control (C2) Maps More Useful

2018 ◽  
Vol 62 (1) ◽  
pp. 1057-1061 ◽  
Author(s):  
Yuval Zak ◽  
Tal Oron-Gilad ◽  
Yisrael Parmet
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Information Integration ◽  
Information Overload ◽  
Command And Control ◽  
Operator Performance ◽  
Aerial Vehicles ◽  
Mission Success ◽  
Mission Critical ◽  
And Control ◽  
Operator Workload

Command and control (C2) maps in military unmanned aerial vehicles (UAVs) are often cluttered beyond the needs of operators. Unfortunately, information overload increases the operators’ mental effort and mission performance suffers. To make C2 maps more useful and improve operator performance, this study proposes a triangular approach to highlighting mission-critical information. First, the underlying value of map information and its relevance to mission success are examined. Second, algorithms based on machine learning are developed to facilitate information integration and generate visualization items, via tagging in time and space, where the appropriate area of relevance for each item is defined. Third, the algorithms are improved to dynamically update the visualizations. The proposed approach and developed algorithms are being evaluated based on four experiments with professional operators in simulated UAV and C2 environments. Hopefully, it would be possible to generalize the algorithms developed in this research-in-progress to other spatial and temporal domains where workload must be reduced.

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