On extended state based Kalman filter for nonlinear time-varying uncertain systems with measurement bias
Xiaocheng Zhang
Wenchao Xue
Hai-Tao Fang
LSC,NCMIS,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,China;School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing,China
摘要：This paper addresses the state estimation for a class of nonlinear time-varying stochastic systems with both uncertain dynam-ics and unknown measurement bias.A novel extended state based Kalman filter(ESKF)algorithm is developed to estimate the original state,the uncertain dynamics and the measurement bias.It is shown that the estimation error of the proposed algorithm is bounded in the mean square sense.Also,the estimation of the measurement bias asymptotically converges to its true value,such that the influence of measurement bias is eliminated.Furthermore,the asymptotic optimality of the estima-tion result is proved while the uncertain dynamics approaches to a constant vector.Finally,a simulation study for harmonic oscillator system model is provided to illustrate the effectiveness of proposed method.
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论文发表日期：2021-02-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：11( 142-152 )
英文信息