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Wyszukujesz frazę "model estimation" wg kryterium: Temat


Wyświetlanie 1-6 z 6
Tytuł:
Integrated estimation model of clean coal ash content for froth flotation based on model updating and multiple LS-SVMs
Autorzy:
Dong, Zhiyong
Wang, Ranfeng
Fan, Minqiang
Fu, Xiang
Geng, Shaowei
Powiązania:
https://bibliotekanauki.pl/articles/110152.pdf
Data publikacji:
2019
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
flotation
clean coal ash content
integrated estimation model
multiple LS-SVMs
Opis:
Clean coal ash content, a prominent product index describing coal froth flotation, is difficult to be measured online. This constraint leads to a lack of timely guidance during operation and impedes the optimal operation of the coal flotation process. To solve this problem, considering the fluctuation of working conditions, the heterogeneity of raw coal and the variation of feed coal classes, an integrated estimation model of clean coal ash content for coal flotation based on model updating and multiple least squares support vector machines (LS-SVMs) is proposed. First, a single estimation model for a single class of coal based on LS-SVM is built, and the internal parameters are optimized by gravitational search algorithm (GSA). Second, the model updating strategy is designed to solve the problem of the decline in single model accuracy. Furthermore, a multiple LS-SVMs model formed by several single models for different classes of coal is studied along with the model switching mechanism to address the problem of model mismatch. Finally, an industrial experiment and evaluation are conducted. The mean relative error between the estimated and actual values is 3.32%, and the correlation coefficient is 0.9331. The estimation accuracy and adaptability of the integrated model can meet the industrial requirements.
Źródło:
Physicochemical Problems of Mineral Processing; 2019, 55, 1; 21-37
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Very-Low-Speed Sensorless Control Induction Motor Drive with Online Rotor Resistance Tuning by Using MRAS Scheme
Autorzy:
Zorgani, Youssef Agrebi
Jouili, Mabrouk
Koubaa, Yassine
Boussak, Mohamed
Powiązania:
https://bibliotekanauki.pl/articles/1193692.pdf
Data publikacji:
2019
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
induction motor
stator flux orientation model
model reference adaptive system
MRAS
rotor speed estimation
resistance estimation
programmable cascaded low-pass filters
PCLPF
Opis:
A sensorless indirect stator-flux-oriented control (ISFOC) induction motor drive at very low frequencies is presented herein. The model reference adaptive system (MRAS) scheme is used to estimate the speed and the rotor resistance simultaneously. However, the error between the reference and the adjustable models, which are developed in the stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimates of speed and the rotor resistance from the stator voltage and the machine current measurements. The stator flux components in the stationary reference frame are estimated through a pure integration of the back electro-motive force (EMF) of the machine. When the machine is operated at low speed, the pure integration of the back EMF introduces an error in flux estimation which affects the performance torque and speed control. To overcome this problem, pure integration is replaced with a programmable cascaded low-pass filter (PCLPF). The stability analysis method of the MRAS estimator is verified in order to show the robustness of the rotor resistance variations. Experimental results are presented to prove the effectiveness and validity of the proposed scheme of sensorless ISFOC induction motor drive.
Źródło:
Power Electronics and Drives; 2019, 4, 39; 125-140
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A very-low-speed sensorless control induction motor drive with online rotor resistance tuning by using MRAS scheme
Autorzy:
Agrebi Zorgani, Y.
Jouili, M.
Koubaa, Y.
Boussak, M.
Powiązania:
https://bibliotekanauki.pl/articles/1193675.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
induction motor
stator flux orientation model
model reference adaptive system
MRAS
rotor speed estimation
resistance estimation
programmable cascaded low-pass filters
PCLPF
Opis:
A sensorless indirect stator-flux-oriented control (ISFOC) induction motor drive at very low frequencies is presented herein. The model reference adaptive system (MRAS) scheme is used to estimate the speed and the rotor resistance simultaneously. However, the error between the reference and the adjustable models, which are developed in the stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimates of speed and the rotor resistance from the stator voltage and the machine current measurements. The stator flux components in the stationary reference frame are estimated through a pure integration of the back electro-motive force (EMF) of the machine. When the machine is operated at low speed, the pure integration of the back EMF introduces an error in flux estimation which affects the performance torque and speed control. To overcome this problem, pure integration is replaced with a programmable cascaded low-pass filter (PCLPF). The stability analysis method of the MRAS estimator is verified in order to show the robustness of the rotor resistance variations. Experimental results are presented to prove the effectiveness and validity of the proposed scheme of sensorless ISFOC induction motor drive.
Źródło:
Power Electronics and Drives; 2018, 3, 38; 171-186
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Estimation of composite load model parameters using improved particle swarm optimization
Autorzy:
Regulski, P.
Gonzalez-Longatt, F.
Terzija, V.
Powiązania:
https://bibliotekanauki.pl/articles/410557.pdf
Data publikacji:
2012
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
load modeling
parameter estimation
particle swarm optimization (PSO)
composite load model
Opis:
Power system loads are one of its crucial elements to be modeled in stability studies. However their static and dynamic characteristics are very often unknown and usually changing in time (daily, weekly, monthly and seasonal variations). Taking this into account, a measurement-based approach for determining the load characteristics seems to be the best practice, as it updates the parameters of a load model directly from the system measurements. To achieve this, a Parameter Estimation tool is required, so a common approach is to incorporate the standard Nonlinear Least Squares, or Genetic Algorithms, as a method providing more global capabilities. In this paper a new solution is proposed -an Improved Particle Swarm Optimization method. This method is an Artificial Intelligence type technique similar to Genetic Algorithms, but easier for implementation and also computationally more efficient. The paper provides results of several experiments proving that the proposed method can achieve higher accuracy and show better generalization capabilities than the Nonlinear Least Squares method. The computer simulations were carried out using a one-bus and an IEEE 39-bus test system.
Źródło:
Present Problems of Power System Control; 2012, 2; 41-51
2084-2201
Pojawia się w:
Present Problems of Power System Control
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sensorless Induction Motor Drive Based on Model Reference Adaptive System Scheme Utilising a Fictitious Resistance
Autorzy:
Hajji, Soufien
Chehida, Ramzi Ben
Zayani, Hichem
Bouaziz, Noomen
Zorgani, Youssef Agrebi
Powiązania:
https://bibliotekanauki.pl/articles/1193902.pdf
Data publikacji:
2020
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
indirect stator flux-oriented controller model
ISFOC model
model reference adaptive system
MRAS
fictitious resistance
rotor speed estimation
induction motor
IM
Opis:
This article presents a new development of an indirect stator flux-oriented controller for sensorless speed induction motor drive utilising instantaneous and steady-state values, respectively, of a fictitious resistance symbolised as R_f. The dimension of the fictitious quantity, in this context, is the ohm, which is the difference between the stator d- and q-axis fictitious resistances. However, from the measurement of the stator voltage and currents of the machine, two independent resistance estimators are built. Therefore, the first is considered as a reference model of the induction machine (IM), and the second is considered as an adjustable model. Subsequently, the error between the states of the two models is used to drive a suitable adaptation mechanism that generates the estimation of the speed, for the adjustable model. Furthermore, the structure of the proposed estimator is free from stator resistance and eliminates the requirement of any flux computation. All the detailed simulation study is carried out in MATLAB/Simulink to validate the proposed method and to highlight the robustness and the stability of the proposed model reference adaptive system estimator.
Źródło:
Power Electronics and Drives; 2020, 5, 40; 199-212
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Frequentist inference on traffic intensity of M/M/1 queuing system
Autorzy:
Dutta, Kaustav
Choudhury, Amit
Powiązania:
https://bibliotekanauki.pl/articles/2204097.pdf
Data publikacji:
2023
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
confidence interval
estimation
hypothesis testing
performance measures
single server Markovian model
traffic intensity
Opis:
When we study any queuing system, the performance measures reflect different features of the system. In the classical M/M/1 queuing system, traffic intensity is perhaps the most important performance measure. We propose a fresh and simple estimator for the same and show that it has nice properties. Our approach is frequentist. This approach has the dual advantage of practical usability and familiarity. Our proposed estimator is attractive as it possesses desirable properties. We have shown how our estimator lends itself to testing of hypothesis. Confidence intervals are constructed. Sample size determination is also discussed. A comparison with a few similar estimators is also performed.
Źródło:
Operations Research and Decisions; 2023, 33, 1; 21--34
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-6 z 6

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