Analysis of Dynamic Errors in Estimating Parameters of Structurally Uncertain Measurement Processes Based on Quasioptimal Intellectual Algorithms of Combined Maximum Principle

被引:0
|
作者
Kostoglotov, A. [1 ]
Lazarenko, S. [1 ]
Pugachev, I [1 ]
Kornev, A. [2 ]
机构
[1] Rostov State Transport Univ, Don State Tech Univ, Rostov Na Donu, Russia
[2] Minist Def, Main Sci Metrol Ctr, Fed State Budgetary Inst, Mytishchi, Russia
关键词
adaptive dynamic filter; dynamic error; dynamic motion model; estimation; missing data; the variational Hamilton-Ostrogradsky principle; structural uncertainty; SYSTEMS;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Measurement processes which structural uncertainties are due to missing data, missed information in measurements, etc. are considered. A new algorithm for estimating the parameters of measurement processes is built on the basis of a structurally-adaptive model with dynamic properties which are due to the correspondence to the Hamilton-Ostrogradsky principle. The intellectual properties of the estimation appear in the adaptation of the dynamics of an evolutionary model to the dynamics of the occurring measurement processes. Mathematical modeling shows that their use makes it possible to reduce the errors in the estimation of dynamic processes compare to the "alpha-beta" filter under conditions of missing data by an average of 12%.
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页数:5
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