模型与过程特征在集值动态系统状态估计中的应用

E. Podivilova, V. Shiryaev
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引用次数: 1

摘要

研究了集值动态系统状态估计问题。已知的集值动态系统状态估计算法是在扰动和噪声的数学模型未知但其可能值集已知的情况下发展起来的。对干扰和噪声的所有可能值计算集值估计。然而,关于干扰和噪声特性的一些附加信息是可用的。关于不确定系统参数的附加信息可以用来降低计算复杂度和提高估计的准确性。
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Application of model and process features in set-valued dynamical system state estimation
The article deals with the issue of set-valued dynamical system state estimation. The known algorithms of set-valued dynamical system state estimation are developed when the mathematical model of disturbances and noises is unknown but the sets of their possible values are available. The set-valued estimate is computed for all possible values of disturbances and noises. However, some additional information on the character of disturbances and noises can be available. Additional information about uncertain system parameters can be used to reduce computational complexity and to increase estimates accuracy.
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