Real-Time Software for Implementation of Feedback Control

2017 ◽  
pp. 16-1-16-32 ◽  
Author(s):  
David M. Auslander ◽  
John R. Ridgely ◽  
Jason C. Jones
Keyword(s):  
Feedback Control ◽  
Real Time

scholarly journals Real‐time feedback control of voice in cochlear implant recipients

2020 ◽  
Vol 5 (6) ◽  
pp. 1156-1162
Author(s):  
Anirudh Gautam ◽  
Jason A. Brant ◽  
Michael J. Ruckenstein ◽  
Steven J. Eliades
Keyword(s):  
Feedback Control ◽  
Cochlear Implant ◽  
Real Time

scholarly journals RTLIO: Real-Time LiDAR-Inertial Odometry and Mapping for UAVs

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3955
Author(s):  
Jung-Cheng Yang ◽  
Chun-Jung Lin ◽  
Bing-Yuan You ◽  
Yin-Long Yan ◽  
Teng-Hu Cheng
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
High Frequency ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Sampling Rate ◽  
Outdoor Environment ◽  
Position Accuracy ◽  
Graph Optimization ◽  
Pose Graph Optimization

Most UAVs rely on GPS for localization in an outdoor environment. However, in GPS-denied environment, other sources of localization are required for UAVs to conduct feedback control and navigation. LiDAR has been used for indoor localization, but the sampling rate is usually too low for feedback control of UAVs. To compensate this drawback, IMU sensors are usually fused to generate high-frequency odometry, with only few extra computation resources. To achieve this goal, a real-time LiDAR inertial odometer system (RTLIO) is developed in this work to generate high-precision and high-frequency odometry for the feedback control of UAVs in an indoor environment, and this is achieved by solving cost functions that consist of the LiDAR and IMU residuals. Compared to the traditional LIO approach, the initialization process of the developed RTLIO can be achieved, even when the device is stationary. To further reduce the accumulated pose errors, loop closure and pose-graph optimization are also developed in RTLIO. To demonstrate the efficacy of the developed RTLIO, experiments with long-range trajectory are conducted, and the results indicate that the RTLIO can outperform LIO with a smaller drift. Experiments with odometry benchmark dataset (i.e., KITTI) are also conducted to compare the performance with other methods, and the results show that the RTLIO can outperform ALOAM and LOAM in terms of exhibiting a smaller time delay and greater position accuracy.

Real-time feedback control system for ADITYA-U horizontal plasma position stabilisation

2021 ◽  
Vol 165 ◽  
pp. 112218
Author(s):  
Rohit Kumar ◽  
Pramila Gautam ◽  
Shivam Gupta ◽  
R.L. Tanna ◽  
Praveenlal Edappala ◽  
...  
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Real Time ◽  
Feedback Control System ◽  
Plasma Position

scholarly journals RISE Feedback Control of Cable-Driven Parallel Robots: Design and Real-Time Experiments

2020 ◽  
Vol 53 (2) ◽  
pp. 8519-8524
Author(s):  
G. Hassan ◽  
A. Chemori ◽  
L. Chikh ◽  
P.E. Hervé ◽  
M. El Rafei ◽  
...  
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
Parallel Robots

Real-time state estimation and feedback control of an oscillating qubit via self-fulfilling prophecy (SFP)

Metrologia ◽  
2019 ◽  
Vol 56 (1) ◽  
pp. 014003 ◽  
Author(s):  
Pieter J W du Toit ◽  
Shaun C Burd ◽  
Thomas Konrad ◽  
Hermann Uys
Keyword(s):  
Feedback Control ◽  
State Estimation ◽  
Real Time

scholarly journals Real-Time Genetic Compensation Defines the Dynamic Demands of Feedback Control

Cell ◽  
2018 ◽  
Vol 175 (3) ◽  
pp. 877-886.e10 ◽  
Author(s):  
Patrick Harrigan ◽  
Hiten D. Madhani ◽  
Hana El-Samad
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
Genetic Compensation
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