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Tytuł:
Recursive Identification of Wiener Systems
Autorzy:
Greblicki, W.
Powiązania:
https://bibliotekanauki.pl/articles/908066.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system Wienera
metoda nieparametryczna
Wiener system
system identification
recursive identification
nonparametric identification
Opis:
A Wiener system, i.e. a cascade system consisting of a linear dynamic subsystem and a nonlinear memoryless subsystem is identified. The a priori information is nonparametric, i.e. neither the functional form of the nonlinear characteristic nor the order of the dynamic part are known. Both the input signal and the disturbance are Gaussian white random processes. Recursive algorithms to estimate the nonlinear characteristic are proposed and their convergence is shown. Results of numerical simulation are also given. A known algorithm recovering the impulse response of the dynamic part is presented in a recursive form.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 4; 977-991
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System Identification from Multiple-Trial Data Corrupted by Non-Repeating Periodic Disturbances
Autorzy:
Phan, M. Q.
Longman, R. W.
Lee, S. C.
Lee, J. W.
Powiązania:
https://bibliotekanauki.pl/articles/908209.pdf
Data publikacji:
2003
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
automatyka
robotyka
system identification
disturbance identification
iterative learning control
repetitive control
interaction matrix
Opis:
Iterative learning and repetitive control aim to eliminate the effect of unwanted disturbances over repeated trials or cycles. The disturbance-free system model, if known, can be used in a model-based iterative learning or repetitive control system to eliminate the unwanted disturbances. In the case of periodic disturbances, although the unknown disturbance frequencies may be the same from trial to trial, the disturbance amplitudes, phases, and biases do not necessarily repeat. Furthermore, the system may not return to the same initial state at the end of each trial before starting the next trial. In spite of these constraints, this paper shows how to identify the system disturbance-free dynamics from disturbance-corrupted input-output data collected over multiple trials without having to measure the disturbances directly. The system disturbance-free model can then be used to identify the disturbances as well, for use in learning or repetitive control. This paper represents the first extension of the interaction matrix approach to the multiple-trial environment of iterative learning control.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2003, 13, 2; 185-192
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear system identification using heterogeneous multiple models
Autorzy:
Orjuela, R.
Marx, B.
Ragot, J.
Maquin, D.
Powiązania:
https://bibliotekanauki.pl/articles/330794.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
nonlinear system identification
multiple model
heterogeneous submodel
układ nieliniowy
model wielokrotny
podmodel heterogeniczny
Opis:
Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state spaces are not the same and consequently they can be of various dimensions. Thanks to this feature, the complexity of the submodels can be well adapted to that of the nonlinear system introducing flexibility and generality in the modelling stage. This paper deals with off-line identification of nonlinear systems based on heterogeneous multiple models. Three optimisation criteria (global, local and combined) are investigated to obtain the submodel parameters according to the expected modelling performances. Particular attention is paid to the potential problems encountered in the identification procedure with a special focus on an undesirable phenomenon called the no output tracking effect. The origin of this difficulty is explained and an effective solution is suggested to overcome this problem in the identification task. The abilities of the model are finally illustrated via relevant identification examples showing the effectiveness of the proposed methods.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2013, 23, 1; 103-115
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear MISO glass melting process
Autorzy:
Byrski, Witold
Drapała, Michał
Byrski, Jędrzej
Powiązania:
https://bibliotekanauki.pl/articles/907805.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
continuous system
modulating functions
system identification
exact state observer
glass forehearths
układ ciągły
identyfikacja systemu
dokładny obserwator stanu
Opis:
The paper presents new concepts of the identification method based on modulating functions and exact state observers with its application for identification of a real continuous-time industrial process. The method enables transformation of a system of differential equations into an algebraic one with the same parameters. Then, these parameters can be estimated using the least-squares approach. The main problem is the nonlinearity of the MISO process and its noticeable transport delays. It requires specific modifications to be introduced into the basic identification algorithm. The main goal of the method is to obtain on-line a temporary linear model of the process around the selected operating point, because fast methods for tuning PID controller parameters for such a model are well known. Hence, a special adaptive identification approach with a moving window is proposed, which involves using on-line registered input and output process data. An optimal identification method for a MISO model assuming decomposition to many inner SISO systems is presented. Additionally, a special version of the modulating functions method, in which both model parameters and unknown delays are identified, is tested on real data sets collected from a glass melting installation.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 4; 739-757
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Linear-wavelet networks
Autorzy:
Galvao, R. K. H.
Becerra, V. M.
Calado, J. M. F.
Silva, P. M.
Powiązania:
https://bibliotekanauki.pl/articles/907399.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sieć falkowa
model nieliniowy
analiza regresji
identyfikacja systemu
wavelet networks
nonlinear models
regression analysis
system identification
Opis:
This paper proposes a nonlinear regression structure comprising a wavelet network and a linear term. The introduction of the linear term is aimed at providing a more parsimonious interpolation in high-dimensional spaces when the modelling samples are sparse. A constructive procedure for building such structures, termed linear-wavelet networks, is described. For illustration, the proposed procedure is employed in the framework of dynamic system identification. In an example involving a simulated fermentation process, it is shown that a linear-wavelet network yields a smaller approximation error when compared with a wavelet network with the same number of regressors. The proposed technique is also applied to the identification of a pressure plant from experimental data. In this case, the results show that the introduction of wavelets considerably improves the prediction ability of a linear model. Standard errors on the estimated model coefficients are also calculated to assess the numerical conditioning of the identification process.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2004, 14, 2; 221-232
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Estimation of feedwater heater parameters based on a grey-box approach
Autorzy:
Barszcz, T.
Czop, P.
Powiązania:
https://bibliotekanauki.pl/articles/930137.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
identyfikacja systemu
wymiennik ciepła
szara skrzynka
first-principle model
system identification
heater
heat exchanger
grey box
Opis:
The first-principle modeling of a feedwater heater operating in a coal-fired power unit is presented, along with a theoretical discussion concerning its structural simplifications, parameter estimation, and dynamical validation. The model is a part of the component library of modeling environments, called the Virtual Power Plant (VPP). The main purpose of the VPP is simulation of power generation installations intended for early warning diagnostic applications. The model was developed in the Matlab/Simulink package. There are two common problems associated with the modeling of dynamic systems. If an analytical model is chosen, it is very costly to determine all model parameters and that often prevents this approach from being used. If a data model is chosen, one does not have a clear interpretation of the model parameters. The paper uses the so-called grey-box approach, which combines first-principle and data-driven models. The model is represented by nonlinear state-space equations with geometrical and physical parameters deduced from the available documentation of a feedwater heater, as well as adjustable phenomenological parameters (i.e., heat transfer coefficients) that are estimated from measurement data. The paper presents the background of the method, its implementation in the Matlab/Simulink environment, the results of parameter estimation, and a discussion concerning the accuracy of the method.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2011, 21, 4; 703-715
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Parameter identification and estimation for stage-structured population models
Autorzy:
Coll, Carmen
Sánchez, Elena
Powiązania:
https://bibliotekanauki.pl/articles/331082.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system identification
parameter estimation
dynamic population
discrete time system
rank-one matrix
identyfikacja systemu
estymacja parametru
dynamika populacji
system czasu dyskretnego
Opis:
A stage-structured population model with unknown parameters is considered. Our purpose is to study the identifiability of the model and to develop a parameter estimation procedure. First, we analyze whether the parameter vector can or cannot uniquely be determined with the knowledge of the input-output behavior of the model. Second, we analyze how the information in the experimental data is translated into the parameters of the model. Furthermore, we propose a process to improve the recursive values of the parameters when successive observation data are considered. The structure of the state matrix leads to an analysis of the inverse of a sum of rank-one matrices.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 2; 327-336
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of Dynamic Neural Networks With Application to Observer-Based Fault Detection and Izolation
Autorzy:
Marcu, T.
Mirea, L.
Frank, P. M.
Powiązania:
https://bibliotekanauki.pl/articles/908286.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
wykrywanie błędu
sieć neuronowa dynamiczna
identyfikacja systemu
fault diagnosis
dynamic neural networks
system identification
static neural classifiers
three-tank system
Opis:
The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The main emphasis is placed upon the development of neural observer schemes. They are built based on dynamic neural networks, i.e. dynamic multi-layer perceptrons with mixed structure. The goal is to achieve an adequate approximation of process outputs for known classes of the process behaviour. The obtained symptoms are then classified by means of static artificial nets. Appropriate decision mechanisms are designed for each type of observer schemes. An application to a laboratory process is included. It refers to component and instrument fault detection and isolation in a three-tank system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 547-570
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonparametric instrumental variables for identification of block-oriented systems
Autorzy:
Mzyk, G.
Powiązania:
https://bibliotekanauki.pl/articles/330283.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system identification
instrumental variables
NARMAX system
Hammerstein system
Wiener system
Lur'e system
nonparametric method
identyfikacja systemu
zmienna instrumentalna
system Hammersteina
system Wienera
metoda nieparametryczna
Opis:
A combined, parametric-nonparametric identification algorithm for a special case of NARMAX systems is proposed. The parameters of individual blocks are aggregated in one matrix (including mixed products of parameters). The matrix is estimated by an instrumental variables technique with the instruments generated by a nonparametric kernel method. Finally, the result is decomposed to obtain parameters of the system elements. The consistency of the proposed estimate is proved and the rate of convergence is analyzed. Also, the form of optimal instrumental variables is established and the method of their approximate generation is proposed. The idea of nonparametric generation of instrumental variables guarantees that the I.V. estimate is well defined, improves the behaviour of the least-squares method and allows reducing the estimation error. The method is simple in implementation and robust to the correlated noise.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2013, 23, 3; 521-537
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection
Autorzy:
Mrugalski, M.
Powiązania:
https://bibliotekanauki.pl/articles/331364.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
robust fault detection
nonlinear system identification
dynamic GMDH neural network
unscented Kalman filter
detekcja uszkodzeń
identyfikacja nieliniowa
sieć neuronowa dynamiczna
filtr Kalmana bezśladowy
Opis:
This paper presents an identification method of dynamic systems based on a group method of data handling approach. In particular, a new structure of the dynamic multi-input multi-output neuron in a state-space representation is proposed. Moreover, a new training algorithm of the neural network based on the unscented Kalman filter is presented. The final part of the work contains an illustrative example regarding the application of the proposed approach to robust fault detection of a tunnel furnace.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2013, 23, 1; 157-169
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A comparative and experimental study on gradient and genetic optimization algorithms for parameter identification of linear MIMO models of a drilling vessel
Autorzy:
Bańka, S.
Brasel, M.
Dworak, P.
Jaroszewski, K.
Powiązania:
https://bibliotekanauki.pl/articles/329756.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
MIMO dynamic plant
identification
nonlinear system
system MIMO
identyfikacja parametryczna
układ nieliniowy
Opis:
The paper presents algorithms for parameter identification of linear vessel models being in force for the current operating point of a ship. Advantages and disadvantages of gradient and genetic algorithms in identifying the model parameters are discussed. The study is supported by presentation of identification results for a nonlinear model of a drilling vessel.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 877-893
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Recursive identification algorithm for dynamic systems with output backlash and its convergence
Autorzy:
Dong, R.
Tan, Q.
Tan, Y.
Powiązania:
https://bibliotekanauki.pl/articles/930007.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system nieliniowy
luz
identyfikacja rekurencyjna
nonlinear system
backlash
recursive identification
pseudo-Wiener model
Opis:
This paper proposes a recursive identification method for systems with output backlash that can be described by a pseudo-Wiener model. In this method, a novel description of the nonlinear part of the system, i.e., backlash, is developed. In this case, the nonlinear system is decomposed into a piecewise linearized model. Then, a modified recursive general identification algorithm (MRGIA) is employed to estimate the parameters of the proposed model. Furthermore, the convergence of the MRGIA for the pseudo-Wiener system with backlash is analysed. Finally, a numerical example is presented.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2009, 19, 4; 631-638
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Identification of steady and non-steady gait of human-exoskeleton walking system
Autorzy:
Żur, K. K.
Powiązania:
https://bibliotekanauki.pl/articles/264542.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
identyfikacja
egzoszkielet
system sterowania
identification
steady gait
non-steady gait
exoskeleton
Opis:
In this paper a method of analysis of exoskeleton multistep locomotion was presented by using a computer with the preinstalled DChC program. The paper also presents a way to analytically calculate the “,motion indicator”, as well as the algorithm calculating its two derivatives. The algorithm developed by the author processes data collected from the investigation and then a program presents the obtained final results. Research into steady and non-steady multistep locomotion can be used to design two-legged robots of DAR type and exoskeleton control system.
Źródło:
International Journal of Applied Mechanics and Engineering; 2013, 18, 3; 923-933
1734-4492
2353-9003
Pojawia się w:
International Journal of Applied Mechanics and Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Gram-Schmidt Method in the Identification of a Generalized Control System
Autorzy:
Wysocki, H.
Powiązania:
https://bibliotekanauki.pl/articles/911169.pdf
Data publikacji:
2000
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
rachunek operatorowy
pochodna
system sterowania
operational calculus
derivative
integral
limit condition
control system
identification
orthonormalization method
Opis:
This article discusses the identification of a generalized linear control system described in the Bittner operational calculus by an abstract linear differential equation with constant coefficients. The identification problem leads to that of the best approximation in the vector space l_m^2 and is solved by using the Gram-Schmidt orthonormalization method. The classical Strejc method and the Shinbrot modulating function method are generalized here.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2000, 10, 2; 245-271
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Range Identification for a Perspective Dynamic System with a Single Homogeneous Observation
Autorzy:
Ma, L.
Chen, Y.
Moore, K. L.
Powiązania:
https://bibliotekanauki.pl/articles/908492.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system identyfikacji
układ dynamiczny
obserwator nieliniowy
range identification
perspective dynamic systems
nonlinear observer
Opis:
Perspective problems arise in machine vision when using a camera to observe the scene. Essential problems include the identification of unknown states and/or unknown parameters from perspective observations. Range identification is used to estimate the states/positions of a moving object with known motion parameters. Range estimation has been discussed in the literature using nonlinear observers with full homogeneous observations derived from the image plane. In this paper, the same range identification problem is discussed with a single homogeneous observation using nonlinear observers. Our simulation results verify the convergence of the observers when their observability conditions are satisfied.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 1; 63-72
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 21

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