Adaptive feed-forward control for inertially stabilized platform

2015 ◽  
Vol 23 (1) ◽  
pp. 141-148 ◽  
Author(s):  
朱明超 ZHU Ming-chao ◽  
刘慧 LIU Hui ◽  
张鑫 ZHANG Xin ◽  
贾宏光 JIA Hong-guang
2018 ◽  
Vol 198 ◽  
pp. 01005
Author(s):  
WeiMing Zhang ◽  
ZeLin Shi

Due to the mass imbalance about the center of rotation, the stability of stabilized platform system degrades with carrier’s disturbances. Various feed-forward control methods are provided by reaserchers to solve this problem, however these methods are not well applied because the eccentricity of stabilized platform could not be measured directly. The dynamics model of a typical 2-axis stabilized platform is given. The eccentricity vector is identified through Unscented Kalman Filter(UKF) algorithm. Imbalance torque is precisely observed so that the real-time nonlinear compensation for mass imbalance is achieved through a feed-forward loop. The simulation result indicates that the Root Mean Squared Error (RMSE) of parameters estimation is 0.024 after convergence. the LOS stabilization with carrier’s 2.5Hz vibration is 0.04 rad/s, which improves 78% compared to conventional feed-back control.


2020 ◽  
Vol 53 (2) ◽  
pp. 1331-1336
Author(s):  
Sven Pfeiffer ◽  
Annika Eichler ◽  
Holger Schlarb

2014 ◽  
Vol 989-994 ◽  
pp. 3386-3389
Author(s):  
Zhu Wen Yan ◽  
Hen An Bu ◽  
Dian Hua Zhang ◽  
Jie Sun

The influence on the shape of the strip from rolling force fluctuations has been analyzed. The combination of intermediate roll bending and work roll bending has been adopted. The principle of rolling force feed-forward control has been analyzed. The feed-forward control model has been established on the basis of neural networks. The model has been successfully applied to a rolling mill and a good effect has been achieved.


2010 ◽  
Vol 32 (10) ◽  
pp. 1678-1685 ◽  
Author(s):  
Jason B. Carmel ◽  
Sangsoo Kim ◽  
Marcel Brus-Ramer ◽  
John H. Martin

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