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首页> 外文期刊>IEEE Transactions on Automatic Control >Robust, reduced-order, nonstrictly proper state estimation via the optimal projection equations with guaranteed cost bounds
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Robust, reduced-order, nonstrictly proper state estimation via the optimal projection equations with guaranteed cost bounds

机译:通过具有保证成本边界的最优投影方程进行稳健,降阶,非严格适当的状态估计

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摘要

A state estimation design problem involving parametric plant uncertainties is considered. An estimation error bound suggested by multiplicative white-noise modeling is utilized for guaranteeing robust estimation over a specified range of parameter uncertainties. Necessary conditions that generalize the optimal projection equations for reduced-order state estimation are used to characterize the estimator that minimizes the error bound. The design equations thus effectively serve as sufficient conditions for synthesizing robust estimators. Additional features include the presence of a static estimation gain in conjunction with the dynamic (Kalman) estimator to obtain a nonstrictly proper estimator.
机译:考虑了涉及参数工厂不确定性的状态估计设计问题。利用乘性白噪声建模建议的估计误差范围用于保证在参数不确定性的指定范围内进行可靠的估计。概括了用于降阶状态估计的最佳投影方程的必要条件用于表征使误差范围最小的估计器。因此,设计方程有效地充当了用于合成鲁棒估计器的充分条件。其他功能包括与动态(Kalman)估计器结合使用的静态估计增益,以获取非严格适当的估计器。

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