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Search results for: IDENTIFICATION OF NONSTATIONARY SYSTEMS
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Identification of Continuous Systems - Practical Issues of Insensitivity to Perturbations
PublicationIn this paper the issue of continuous systems estimation, insensitive to certain perturbations, is discussed. Such an approach has rational advantages, especially when robust schemes are used to assist a target system responsible for industrial diagnostics. This requires that estimated model parameters are generated on-line, and their values are reliable and to a great extent accurate. Practical hints are suggested to challenge...
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A New Method of Noncausal Identification of Time-varying Systems
PublicationThe paper shows that the problem of noncausal identification of a time-varying FIR (finite impulse response) sys- tem can be reformulated, and solved, as a problem of smoothing of the preestimated parameter trajectories. Characteristics of the smoothing filter should be chosen so as to provide the best trade- off between the bias and variance of the resulting estimates. It is shown that optimization of the smoothing operation can...
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Identification of continuous systems - Practical issues of insensitivity to perturbations
PublicationIn this paper the issue of continuous systems estimation, insensitive to certain perturbations, is discussed. Such an approach has rational advantages, especially when robust schemes are used to assist a target system responsible for industrial diagnostics. This requires that estimated model parameters are generated on-line, and their values are reliable and to a great extent accurate. Practical hints are suggested to challenge...
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The identification of operational cycles in the monitoring systems of underground vehicles
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On bidirectional preestimates and their application to identification of fast time-varying systems
PublicationWhen applied to the identification of time-varying systems, such as rapidly fading telecommunication channels, adaptive estimation algorithms built on the local basis function (LBF) principle yield excellent tracking performance but are computationally demanding. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a substantial reduction in complexity without significant performance...
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Variable-structure algorithm for identification of quasi-periodically varying systems
PublicationThe paper presents a variable-structure version of a generalized notchfiltering (GANF) algorithm. Generalized notch filters are used for identification of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The proposed algorithm is a cascade of two GANF filters: a multiple-frequency "precise" filter bank, used for precise system tracking, and a...
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Identification of advanced manufacturing systems change factors - methodical aspects
PublicationCelem publikacji jest przedstawienie założeń metodyki identyfikacji kluczowych czynników zmian zaawansowanego systemu produkcyjnego. W publikacji przedstawiono zmiany występujące w otoczeniu przedsiębiorstwa związane z następującymi procesami globalizacji, wirtualizacji, sieciowości i narastającym znaczeniem inteligentnych organizacji. Wyróżniono wielowymiarowe przestrzenie otoczenia, zarówno tego szerszego, jak i bezpośredniego...
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The use of spectrometric diagnostics in identification of the technical condition of tribological systems
PublicationThe paper presents, as an effect of the analysis of investigation results, a possibility of using the spectrometric diagnostics in the tribological system technical condition supervision arrangement. A model, based on the emission of solid particles in tribological system operation, allows to identify the system technical condition. After the analysis of tests carried out with the use of that model, it has been found that the content...
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Frequency response based identification of fractional order dynamical systems
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Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublicationNoncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothingis based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman filter-based parameter trackers can...