Robust Covariance Intersection Fusion Steady-State Kalman Filter with Uncertain Parameters

摘要：

　　For the linear discrete time-invariant system with uncertain parameters and known noise variances,a robust covariance intersection(CI)fusion steady-state Kalman filter is presented by the new approach of compensating the parameter uncertainties by a fictitious noise.Based on the Lyapunov equation approach,it is proved that for the prescribed upper bound of the fictitious noise variances,there exists a sufficiently small region of uncertain parameters; such that its actual filtering error variances are guaranteed to have a less-conservative upper bound.This region is called the robust region.By the searching method,the robust region can be found.Its robust accuracy is higher than that of each local robust Kalman filter.A Monte-Carlo simulation example shows its effectiveness and the good performance.

关键词： Covariance intersection fusion Robust Kalman filter Uncertain parameters Fictitious noise approach Robust region

作者: Wenjuan Qi Xuemei Wang Wenqiang Liu Zili Deng

作者单位: Department of Automation,Heilongjiang University,150080 Harbin,China

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 13-21

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）