Real-time Landing Gear Control System Based on Adaptive 3D Sensing for Safe Landing of UAV

Author(s):  
Mikihiro Ikura ◽  
Leo Miyashita ◽  
Masatoshi Ishikawa
Author(s):  
Giovanni Jacazio ◽  
Gualtiero Balossini

This paper describes an electronically controlled active force control system that was recently developed to provide real time loading for the tests of a landing gear. As the landing gear moves during the test, a force is generated on the landing gear in order to ensure that its dynamics is identical to that that would occur during its operation in an actual flight. Since landing gear deployment and retraction can occur at different environmental and flight conditions, the load profile that must be developed by the force control system depends on the simulated flight condition and is determined by an appropriate landing gear model. To attain accurate force control, a system was setup comprised of a servovalve controlled hydraulic actuator, force and position sensors, and a high rate digital controller implementing a complex adaptive control law. An excellent accuracy of the load control was eventually achieved for all load profiles occurring on the landing gear.


1989 ◽  
Vol 7 (3) ◽  
pp. 363-367 ◽  
Author(s):  
Takaichi Koyama ◽  
Yoichi Takahashi ◽  
Masahiro Kobayashi ◽  
Junichiro Morisawa

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.


2021 ◽  
Vol 165 ◽  
pp. 112218
Author(s):  
Rohit Kumar ◽  
Pramila Gautam ◽  
Shivam Gupta ◽  
R.L. Tanna ◽  
Praveenlal Edappala ◽  
...  

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