SU-EE-A1-05: A Real-Time Feedback Control Algorithm to Compensate 2D Target Motion with a Dynamic Multileaf Collimator

2008 ◽  
Vol 35 (6Part2) ◽  
pp. 2637-2637
Author(s):  
M Tacke ◽  
S Nill ◽  
U Oelfke
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
Control Algorithm ◽  
Target Motion ◽  
Multileaf Collimator

scholarly journals GoRoSoBo simplified: an accurate feedback control algorithm in real time for irrigation canals

2019 ◽  
Vol 21 (6) ◽  
pp. 945-961
Author(s):  
Enrique Bonet ◽  
Manuel Gómez ◽  
M. T. Yubero ◽  
J. Fernández-Francos
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
Hydraulic System ◽  
Control Algorithm ◽  
Estimation Algorithm ◽  
Computational Time ◽  
Irrigation Canal ◽  
Water Demands ◽  
Short Period ◽  
Control Diagram

Abstract An irrigation canal is a hydraulic system whose main objective is to convey water from a source (dam, river) to different users. Such systems can be very large (several tens or hundreds of kilometers), characterized by time delays and non-linear dynamics, strong unknown perturbations and interactions among subsystems. In order to fulfill the requirements of canal users, the water manager must control all water deliveries during the irrigation cycle (or irrigation program) calculating the gate positions of the canal according to the water demands in real time. Initially, our overall control diagram in real time is mainly represented by two algorithms, the canal survey estimation algorithm (this algorithm estimates the water level and velocity along the irrigation canal during a past time horizon) and GoRoSoBo algorithm (feedback control algorithm operating in real time). Regarding long canals with several gates and pumps operating in a short period of time for a long predictive horizon, the initial version of GoRoSoBo algorithms would spend too much time calculating the canal gate position in real time. This is the reason why we have upgraded the code of the GoRoSoBo algorithm, saving in computational time around 85%, in order to operate in 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

PO-1600: Evaluation of a High Dynamic Multileaf Collimator for Real-Time tumor tracking

2020 ◽  
Vol 152 ◽  
pp. S870-S871
Author(s):  
C. Murillo ◽  
S. Seeber ◽  
P. Haering ◽  
C. Lang ◽  
M. Splinter
Keyword(s):  
Real Time ◽  
Multileaf Collimator ◽  
Tumor Tracking ◽  
High Dynamic

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
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