Variable structure multiple model fixed-interval smoothing  

作　　者：Bolun ZHANG Yongxin GAO Zhansheng DUAN 

机构地区：[1]Faculty of Electronic and Information Engineering,School of Automation Science and Engineering,Xi’an Jiaotong University,Xi'an 710049,China

出　　处：《Chinese Journal of Aeronautics》2023年第2期139-148,共10页中国航空学报（英文版）

基　　金：supported in part by the National Natural Science Foundation of China(No.61773306);the National Key Research and Development Plan,China(Nos.2021YFC2202600 and 2021YFC2202603)。

摘　　要：This paper focuses on fixed-interval smoothing for stochastic hybrid systems.When the truth-mode mismatch is encountered,existing smoothing methods based on fixed structure of model-set have significant performance degradation and are inapplicable.We develop a fixedinterval smoothing method based on forward-and backward-filtering in the Variable Structure Multiple Model(VSMM)framework in this paper.We propose to use the Simplified Equivalent model Interacting Multiple Model(SEIMM)in the forward and the backward filters to handle the difficulty of different mode-sets used in both filters,and design a re-filtering procedure in the model-switching stage to enhance the estimation performance.To improve the computational efficiency,we make the basic model-set adaptive by the Likely-Model Set(LMS)algorithm.It turns out that the smoothing performance is further improved by the LMS due to less competition among models.Simulation results are provided to demonstrate the better performance and the computational efficiency of our proposed smoothing algorithms.

关 键 词：Fixed-interval smoothing Model-set adaptation Multiple model estimation Smoothing algorithm Variable structure 

分 类 号：V2[航空宇航科学技术]