Analysis of convergence of adaptive singlestep algorithms for the identification of nonstationary objects
Journal Title: Восточно-Европейский журнал передовых технологий - Year 2019, Vol 1, Issue 4
Abstract
<p>The study deals with the problem of identification of non-stationary parameters of a linear object which can be described by first-order Markovian model, with the help of the simplest in computational terms single-step adaptive identification algorithms – modified algorithms by Kaczmarz and Nagumo-Noda. These algorithms do not require knowledge of information on the degree of non-stationarity of the studied object. When building the model, they use the information only about one step of measurements. Modification involves the use of the regularizing addition in the algorithms to improve their computing properties and avoid division by zero. Using a Markovian model is quite effective because it makes it possible to obtain analytic estimates of the properties of algorithms.</p><p>It was shown that the use of regularizing additions in identification algorithms, while improving stability of algorithms, leads to some slowdown of the process of model construction. The conditions for convergence of regularizing algorithms by Kaczmarz and Nagumo-Noda at the evaluation of stationary parameters in mean and root-mean-square and existing measurement interference were determined.</p>The obtained estimates differ from the existing ones by higher accuracy. Despite this, they are quite general and depend both on the degree of non-stationarity of an object, and on statistical characteristics of interference. In addition, the expressions for the optimal values of the parameters of algorithms, ensuring their maximum rate of convergence under conditions of non-stationarity and the presence of Gaussian interferences, were determined. The obtained analytical expressions contain a series of unknown parameters (estimation error, degree of non-stationarity of an object, statistical characteristics of interferences). For their practical application, it is necessary to use any recurrent procedure for estimation of these unknown parameters and apply the obtained estimates to refine the parameters that are included in the algorithms
Authors and Affiliations
Oleg Rudenko, Oleksandr Bezsonov, Valentyn Lebediev
Keywords
Related Articles
- EP ID EP666176
- DOI 10.15587/1729-4061.2019.157288
- Views 76
- Downloads 0
Development of an intelligent decision support system to control the process of well drilling under complicated conditions
<p>The paper addresses the task on constructing a method for the identification of complications, arising during oil and gas well drilling, which functions under conditions of an a priori and current uncertainty under th...
Development of complex-structure ore deposits by means of chamber systems under conditions of the Kryvyi Rih iron ore field
<p>In order to keep their positions in the world markets, mining enterprises of the Kryvyi Rih iron ore field using the deep-mine method need to develop a resource-saving technology for the development of the fields repr...
Substantiation of correctness and advantages of Lenstra factorization method on Edwards curves
<p>The factorization problem, which is the basis for many classical asymmetric cryptosystems (RSA, Rabin, and others) and a cryptographically strong generator of pseudo-random sequences (PBS), has been investigated in th...
Improving contact durability of polycrystalline systems by controlling the parameters of large-angle grain boundaries
Polycrystalline metal systems in the samples made of steel 40X with different morphology and parameters of the distribution of large-angle grains boundaries for energy have been examined. The effect of the structural-ene...
Development of measures to improve milk quality and safety during production
<p>The number of somatic cells in cow milk affects its quality indicators, grade and safety. The level of somatic cells in milk depends on the state of the udder in animals. That is why it is important to diagnose sub-cl...