Robust time-varying Kalman smoothers with uncertain noise variances
chinese control conference(2021)
摘要
This paper addresses the design of robust Kalman smoothers for the time-varying system with uncertain noise variances. According to the minimax robust estimation principle, and the unbiased linear minimum variance (ULMV) optimal estimation rule, based on the worst-case conservative system with the conservative upper bounds of noise variances, two robust Kalman state smoothing algorithms are presented by the augmented and non-augmented state approaches, respectively. Their robustness is proved by the Lyapunov equation approach, and their robust accuracy relations are proved. A simulation example is given to verify the robustness and the correctness of the robust accuracy relations.
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关键词
Uncertain system,uncertain noise variance,minimax robust estimation,robust accuracy,Lyapunov equation approach,convergence
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