Design of adaptive strong tracking and robust Kalman filter

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所 > 中科院长春光机所知识产出 > 会议论文

	Design of adaptive strong tracking and robust Kalman filter
	Song K. ; Cong S. ; Deng K. ; Shang W. ; Kong D. ; Shen H.
	2014
会议名称	Proceedings of the 33rd Chinese Control Conference, CCC 2014, July 28, 2014 - July 30, 2014
会议地点	Nanjing, China
页码	6626-6631
英文摘要	Only the output noise of system can often be measured in practical application. The disturbance of system state is generally unknown. In this case, the effectiveness of the Kalman filter designed is poor, can not be used, and even causes the divergency. What we do in the process of Kalman filter design is to estimate on-line the unknown disturbance of system state, make use of the improved Sage-Husa state disturbance statistical estimators to estimate the real-time mean and variance of the system state disturbance. In order to further ensure the algorithm robustness to the system disturbance, the strong tracking Kalman filter algorithm was introduced to correct the variance of state prediction in real time. In the application of the velocity model of gyro-stabilized platform with different positive and negative velocity model parameters, we verified the superiority and practicability of the algorithm through comparative experiments under different conditions of the system by the simulation experiments. This paper designs a better Kalman filter with state disturbances and noise, gives a deeply study and investigation by means of the comparative analysis of application performance. 2014 TCCT, CAA.
收录类别	EI
会议录	Proceedings of the 33rd Chinese Control Conference, CCC 2014, July 28, 2014 - July 30, 2014
会议录出版者	IEEE Computer Society
会议录出版地	Nanjing, China
语种	英语
内容类型	会议论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/44608]
专题	长春光学精密机械与物理研究所_中科院长春光机所知识产出_会议论文
推荐引用方式 GB/T 7714	Song K.,Cong S.,Deng K.,et al. Design of adaptive strong tracking and robust Kalman filter[C]. 见:Proceedings of the 33rd Chinese Control Conference, CCC 2014, July 28, 2014 - July 30, 2014. Nanjing, China.