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Search results for: PARAMETER ESTIMATION
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Parameter estimation of a discrete model of a reinforced concrete slab
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Accuracy and parameter estimation of elastic and viscoelastic models of water hammer
PublicationW artykule analizowany jest zagadnienie uderzenia hydraulicznego, stanowiące jeden z najważniejszych problemów nieustalonego przepływu w przewodach pod ciśnieniem. Mimo ponad stuletnich doświadczeń w badaniach zagadnienie to jest ciągle nie w pełni rozpoznane. Może być onio rozpatrywane na dwóch płaszczyznach - praktycznej i teoretycznej. W obu przypadkach na etapie rozwiązania powstają problemy sprawiające, że wyniki nie są satysfakcjonujące....
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Non-quadratic quality criteria in parameter estimation of continuous-time models
PublicationW pracy wykorzystuje się procedury estymacji parametrycznej do identyfikacji modeli z czasem ciągłym. Rozważane algorytmy minimalizują wskaźnik jakości w postaci sumy lub całki wartości bezwzględnej błędu predykcji. Zastosowanie techniki zmiennych instrumentalnych umożliwia ponadto znaczące polepszenie dokładności ocen parametrów, a wprowadzony do w procedur estymacji mechanizm ważenia błędów predykcji pozwala identyfikować modele...
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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Bounding approach to parameter estimation without priori knowledge on model structure error.
PublicationArtykuł przedstawia estymację parametrów modelu ARMA (Autoregresive moving average) metodą zbiorów ograniczonych. Założono brak wiedzy na temat ograniczeń na błąd struktury modelu lub, że wiedza ta jest bardzo konserwatywna. W celu redukcji tego konserwatyzmu, zaproponowano koncepcje modelu punktowo-parametrycznego. W podejściu tym zakłada się istnienie zbioru parametrów modelu oraz błędu struktury odpowiadających każdej z trajektorii...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublicationIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Weighted least squares parameter estimation for model predictive control of integrated wastewater systems at medium time scale.
PublicationW artykule przedstawione zostało sformułowanie i implementacja algorytmu ważonej sumy najmniejszych kwadratów na przesuwnym oknie pomiarowym dla celów estymacji parametrów modelu typu szara skrzynka. Model typu szara skrzynka dynamiki reaktora biologicznego jest wykorzystywany przez moduł sterowania predykcyjnego sterujący zintegrowanym systemem ściekowym w średniej skali czasu. Algorytm estymacji parametrów był walidowany na symulatorze...
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Estimation of a smoothness parameter by spline wavelets
PublicationWe consider the smoothness parameter s*(f) of a function f∈L2(R) in terms of Besov spaces. The existing results on estimation of smoothness [K. Dziedziul, M. Kucharska and B. Wolnik, J. Nonparametric Statist. 23 (2011)] employ the Haar basis and are limited to the case 0
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Bounding approach to parameter estimation without prior knowledge on modeling error and application to quality modeling in drinking water distribution systems
PublicationW artykule rozważana jest estymacja parametrów modelu autoregresji z ruchoma średnią i sygnałem wejściowym (ARMAX) z wykorzystaniem przedziałowego modelu błędu. Zakłada się, że granice błędu struktury modelu są nieznane, bądź znane, ale bardzo konserwatywne. Dla zmniejszenia tego konserwatyzmu proponowane jest idea modeli punktowo-parametrycznych, w której występują zbiory parametrów i błędu modelu odpowiadające wszystkim wejściom....
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Parameter and delay estimation of linear continuous-time systems
PublicationIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous identification...
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Parameter and delay estimation of linear continuous-time systems
PublicationIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is usually described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous...
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On–line Parameter and Delay Estimation of Continuous–Time Dynamic Systems
PublicationThe problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous...
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A framework for accelerated optimization of antennas using design database and initial parameter set estimation
PublicationThe purpose of this paper is to exploit a database of pre-existing designs to accelerate parametric optimization of antenna structures is investigated. Design/methodology/approach The usefulness of pre-existing designs for rapid design of antennas is investigated. The proposed approach exploits the database existing antenna base designs to determine a good starting point for structure optimization and its response sensitivities....
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Novel Interpolation Method of Multi-DFT-Bins for Frequency Estimation of Signal with Parameter Step Change
PublicationThe IpDFT(Interpolation Discrete Fourier Trans-form) method is one of the most commonly used non-parametric methods. However, when a parameter (frequency, amplitude or phase) step changes in the DFT period, the DFT coefficients will be distorted seriously, resulting in the large estimation error of the IpDFT method. Hence, it is a key challenge to find an IpDFT method, which not only can eliminate the effect of the step-changed...
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Set-Bounded joined parameter and state estimation for model predictive control of integrated wastewater treatment plant systems at medium time scale.
PublicationW artykule opisano moduł łącznej estymacji w postaci zbiorów ograniczonych (ang. set-bounded) parametrów i stanu systemu dla potrzeb sterowania predykcyjnego zintegrowanym systemem ściekowym w średniej skali czasu. Jest to jeden ze składowych elementów Inteligentnej Hierarchicznej Struktury Sterowania opracowanej w celu pokonania następujących problemów, które występują w kontrolowanym systemie: różne skale czasowe procesów, silnie...
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Neural-Network-Based Parameter Estimations of Induction Motors
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Density smoothness estimation problem using a wavelet approach
PublicationIn this paper we consider a smoothness parameter estimation problem for a density function. The smoothness parameter of a function is defined in terms of Besov spaces. This paper is an extension of recent results (K. Dziedziul, M. Kucharska, B. Wolnik, Estimation of the smoothness parameter ). The construction of the estimator is based on wavelets coefficients. Although we believe that the effective estimation of the smoothness...
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Estimation of Selected Synchronous Generator Parameters Based on the Gradient Method
PublicationThe authors present a method for the estimation of synchronous generator model parameters using a gradient algorithm. The paper shows an example of model parameter estimation for a turbogenerator and hydrogenerator, based on the generator voltage time responses obtained during an active and reactive power rejection test.
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Estimation of Synchronous Generator and AVR Parameters Based on Gradient and Genetic Methods
PublicationThe author present a method for the estimation of selected synchronous generator model and AVR parameters using a gradient and a genetic algorithm. The paper shows an example of model parameter estimation for a turbogenerator, based on the generator voltage time responses obtained during an active and reactive power rejection test
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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublicationThe problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublicationThe problem of noncausal identification of a time-varying linear system subject to both smooth and occasional jump-type changes is considered and solved using the preestimation technique combined with the basis function approach to modeling the variability of system parameters. The proposed estimation algorithms yield very good parameter tracking results and are computationally attractive.
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Variable-fidelity response feature surrogates for accelerated statistical analysis and yield estimation of compact microwave components
PublicationAccounting for manufacturing tolerances is an essential part of a reliable microwave design process. Yet, quantification of geometry and/or material parameter uncertainties is challenging at the level of full-wave electromagnetic (EM) simulation models. This is due to inherently high cost of EM analysis and massive simulations necessary to conduct the statistical analysis. Here, a low-cost and accurate yield estimation procedure...
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New Approach to Noncasual Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
PublicationIn this technical note, we consider the problem of finite-interval parameter smoothing for a class of nonstationary linear stochastic systems subject to both smooth and abrupt parameter changes. The proposed parallel estimation scheme combines the estimates yielded by several exponentially weighted basis function algorithms. The resulting smoother automatically adjusts its smoothing bandwidth to the type and rate of nonstationarity...
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Radar Signal Parameters Estimation Using Phase Accelerogram in the Time-Frequency Domain
PublicationRadar signal parameter estimation, in the context of the reconstruction of the received signal in a passive radar utilizing other radars as a source of illumination, is one of the fundamental steps in the signal processing chain in such a device. The task is also a crucial one in electronic reconnaissance systems, e.g. ELINT (Electronic Intelligence) systems. In order to obtain accurate results it is important to measure, estimate...
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APPLICATION OF SATELLITE IMAGERY AND GIS TOOLS FOR LAND SURFACE TEMPERATURE ESTIMATION AND VERIFICATION
PublicationLand surface temperature (LST) plays an important role in many land-surface processes on regional as well on global scales. It is also a good indicator of energy flux phenomena and is used as a parameter in various Earth observation related studies. However, LST estimation based on processing and utilisation of satellite derived data constitutes several problems in terms of time limitations, accessibility, atmospheric influence...
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Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array
PublicationThis paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublicationThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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On the preestimation technique and its application to identification of nonstationary systems
PublicationThe problem of noncausal identification of a nonstationary stochastic FIR (finite impulse response) sys- tem is reformulated, and solved, as a problem of smoothing of preestimated parameter trajectories. Three approaches to preestimation are critically analyzed and compared. It is shown that optimization of the smoothing operation can be performed adaptively using the parallel estimation technique. The new approach is computationally...
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At the Limits of Criticality-Based Quantum Metrology: Apparent Super-Heisenberg Scaling Revisited
PublicationWe address the question of whether the super-Heisenberg scaling for quantum estimation is indeed realizable. We unify the results of two approaches. In the first one, the original system is compared with its copy rotated by the parameter-dependent dynamics. If the parameter is coupled to the one-body part of the Hamiltonian, the precision of its estimation is known to scale at most as N−1 (Heisenberg scaling) in terms of the number...
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Decoupled Kalman filter based identification of time-varying FIR systems
PublicationWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Method for the correlation coefficient estimation of the bottom echo signal in the shallow water application using interferometric echo sounder
PublicationThe article presents a new method for the assessment of bottom echo correlation coefficient in the presence of multiple echoes. Bottom correlation coefficient is a parameter that characterizes spatial properties of echo signal. Large variability of the bottom shape or properties (for example caused by the presence of bottom objects) and the presence of the acoustic shadow strongly influence the value of the correlation coefficient....
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Marek Zienkiewicz dr inż.
PeopleDoctor engineer Marek Hubert Zienkiewicz is a graduate of the Faculty of Geodesy, Spatial Engineering and Construction at the University of Warmia and Mazury in Olsztyn. During his engineering, master's and doctoral studies he developed his scientific interests under the supervision of representatives of the Olsztyn geodetic compensatory calculus school. In 2011, he obtained the title of Master of Science in Geodesy and Cartography,...
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The hybrid estimation algorithm for wastewater treatment plant robust model predictive control purposes at medium time scale
PublicationThe paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters...
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A hierarchical observer for a non-linear uncertain CSTR model of biochemical processes
PublicationThe problem of estimation of unmeasured state variables and unknown reaction kinetic functions for selected biochemical processes modelled as a continuous stirred tank reactor is addressed in this paper. In particular, a new hierarchical (sequential) state observer is derived to generate stable and robust estimates of the state variables and kinetic functions. The developed hierarchical observer uses an adjusted asymptotic observer...
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Identification of quasi-periodically varying systems with quasi-linear frequency changes
PublicationThe problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of system parameter estimation can be increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithms can...
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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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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Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublicationWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
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A new look at the statistical identification of nonstationary systems
PublicationThe paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...
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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...
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Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks
PublicationThe rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs....
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this article, specific methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this study, dedicated methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Atmospheric opacity estimation based on IWV derived from GNSS observations for VLBI applications
PublicationThermal emission of atmospheric water vapor has a great influence on the calibration of radio astronomical observations at millimeter wavelengths. The phenomenon of an atmospheric water vapor emits noise signal and attenuates astronomical emission. At 22 GHz, integrated water vapor (IWV) obtained from global navigation satellite systems (GNSS) is strictly related to atmospheric opacity (τ0), which is a crucial parameter for data...
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Influence of Flat Lapping Kinematics on Machinability of Ceramics
PublicationNew tools for flat grinding of ceramics are presented in the paper. Electroplated CBN tools (B64 and B107) were used in a modified single-disc lapping machine configuration. The results from experiments, such as the material removal rate and surface roughness parameters are presented and analyzed. Numerical simulations, based on the model for the shape error and tool wear estimation in machining with flat lapping kinematics, are...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublicationThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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Estimation of groundwater recharge in a shallow sandy aquifer using unsaturated zone modeling and water table fluctuation method
PublicationQuantification of groundwater recharge is one of the most important issues in hydrogeology, especially in view of the ongoing changes in climate and land use. In this study, we use numerical models of 1D vertical flow in the vadose zone and the water table fluctuation (WTF) analysis to investigate local-scale recharge of a shallow sandy aquifer in the Brda outwash plain in northern Poland. We show that these two methods can be...