Central Difference Kalman Filter Approach Based Decentralized Dynamic States Estimator for DFIG Wind Turbines in Power Systems

Author(s):  
Xinqi Fan ◽  
Samson Shenglong Yu ◽  
Tat Kei Chau ◽  
Tyrone Fernando ◽  
Christopher Townsend ◽  
...  
Author(s):  
Jihua Zhu ◽  
Nanning Zheng ◽  
Zejian Yuan ◽  
Qiang Zhang ◽  
Xuetao Zhang ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yong-Gang Zhang ◽  
Yu-Long Huang ◽  
Zhe-Min Wu ◽  
Ning Li

A new moving state marine initial alignment method of strap-down inertial navigation system (SINS) is proposed based on high-degree cubature Kalman filter (CKF), which can capture higher order Taylor expansion terms of nonlinear alignment model than the existing third-degree CKF, unscented Kalman filter and central difference Kalman filter, and improve the accuracy of initial alignment under large heading misalignment angle condition. Simulation results show the efficiency and advantage of the proposed initial alignment method as compared with existing initial alignment methods for the moving state SINS initial alignment with large heading misalignment angle.


2010 ◽  
Vol 44-47 ◽  
pp. 3864-3868
Author(s):  
Ji Cheng Ding ◽  
Lin Zhao ◽  
Jia Liu ◽  
Shuai He Gao

To implement indoor GPS signal tracking in standalone mode when the tracking loop is unlocked and data bit edge is unknown, the paper develops a modified Viterbi Algorithm (MVA) based on dynamic programming, and it was applied for GPS bit synchronization. Besides, two combination carrier tracking schemes based on Central Difference Kalman Filter (CDKF) and MVA module were designed for indoor GPS signal. The testing results indicate that the methods can successful detect bit edge position with high detection probability whether or not the tracking loop is locked. The co-operational tracking scheme is still able to perform when the signal quality deteriorate.


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