ON-LINE ESTIMATION OF BOUNDARY HEAT FLUX OF PARTICIPATING MEDIA BY AN EXTENDED KALMAN FILTERING TECHNIQUE

2019 ◽  
Author(s):  
Shuang Wen ◽  
Hong Qi ◽  
Zhitian Niu ◽  
Yaotao Ren ◽  
Gao-Liang Peng ◽  
...  
Keyword(s):  
Heat Flux ◽  
Kalman Filtering ◽  
Extended Kalman Filtering ◽  
Participating Media ◽  
On Line ◽  
Filtering Technique

Extended Kalman Filtering Technique for the On-line Control of Candida Utilis Production

1985 ◽  
Vol 18 (17) ◽  
pp. 185-189 ◽  
Author(s):  
M. Ghoul ◽  
M.-N. Pons ◽  
J.-M. Engasser ◽  
J. Bordet
Keyword(s):  
Kalman Filtering ◽  
Candida Utilis ◽  
Extended Kalman Filtering ◽  
On Line ◽  
Filtering Technique

Extended Kalman Filtering technique for the on-line control of OKT3 hybridoma cultures

1991 ◽  
Vol 5 (5) ◽  
Author(s):  
Mohamed Ghoul ◽  
Michel Dardenne ◽  
Christian Fonteix ◽  
Annie Marc
Keyword(s):  
Kalman Filtering ◽  
Extended Kalman Filtering ◽  
On Line ◽  
Filtering Technique

scholarly journals Kalman filtering for dynamic motion and model estimation

2021 ◽  
Author(s):  
Randal Schumacher.
Keyword(s):  
Kalman Filtering ◽  
Vision System ◽  
Target Position ◽  
Model Estimation ◽  
Mass Center ◽  
Extended Kalman Filtering ◽  
Dynamic Motion ◽  
Filtering Technique ◽  
Time Determination

The fundamental task of a space vision system for rendezvous, capture, and servicing of satellites on-orbit is the real-time determination of the motion of the target vehicle as observed on-board a chaser vehicle. Augmenting the architecture to incorporate the highly regarded Kalman filtering technique can synthesize a system that is more capable, more efficient and more robust. A filter was designed and testing was conducted in an inertial environment and then in a more realistic relative motion orbital rendezvous scenario. The results indicate that a Dynamic Motion Filter based on extended Kalman filtering can provide the vision system routines with excellent initialization leading to faster convergence, reliable pose estimation at slower sampling rates, and the ability to estimate target position, velocity, orientation, angular velocity, and mass center location.

Dynamic Behavior Analysis of Touchdown Process in Active Magnetic Bearing System Based on Kalman Filtering

2014 ◽  
Author(s):  
Zhe Sun ◽  
Xiao Kang ◽  
Jingjing Zhao ◽  
Guojun Yang ◽  
Zhengang Shi
Keyword(s):  
Dynamic Analysis ◽  
Dynamic Model ◽  
Kalman Filtering ◽  
Experimental System ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Extended Kalman Filtering ◽  
Experiment Data ◽  
Filtering Technique ◽  
Bearing System

Magnetic bearings are widely applied in High Temperature Gas-cooled Reactor (HTGR) and auxiliary bearings are important backup and safety components in AMB systems. The dynamic analysis of the AMB rotors touchdown process is an important foundation for designing auxiliary bearings. In this paper, a data-based dynamic analysis of the touchdown process is proposed. The dynamic model of the touchdown process is firstly established and then the nonlinear extended Kalman filtering technique is applied. Based on the dynamic model and Kalman filtering technique, the proposed method can offer estimations of rotor’s displacements, velocities and accelerations from noisy observations. The proposed method is validated by the experiment data from touchdown experiments. The touchdown experiments are performed on an experimental system with a 440kg heavy rotor, the rotational speed in the experiments is 5000RPM and no brake is applied.

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