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    Wyświetlanie 1-22 z 22
    Tytuł:
    On suppression of chaotic motions of a portal frame structure under non-ideal loading using a magneto-rheological damper
    Autorzy:
    Tusset, A. M.
    Piccirillo, V.
    Balthazar, J. M.
    Brasil, R. M. L. R. F.
    Powiązania:
    https://bibliotekanauki.pl/articles/281951.pdf
    Data publikacji:
    2015
    Wydawca:
    Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
    Tematy:
    feedback control
    feedforward control
    MR damper
    Opis:
    We consider chaotic motions of a portal frame structure under non-ideal loading. To suppress this chaotic behavior, a controlling scheme is implemented. The control strategy involves application of two control signals and nonlinear feedforward control to maintain a desired periodic orbit, and state feedback control to bring the system trajectory into the desired periodic orbit. Additionally, the control strategy includes an active magneto-rheological damper to actuate the system. The control force of the damper is a function of the voltage applied in the coil of the damper that is based on the force given by the controller.
    Źródło:
    Journal of Theoretical and Applied Mechanics; 2015, 53, 3; 653-664
    1429-2955
    Pojawia się w:
    Journal of Theoretical and Applied Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A simplified control strategy for single-phase UPS inverters
    Autorzy:
    Monfared, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/201075.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    single-phase UPS
    multi-loop feedback
    feedforward
    Opis:
    Though there are many strategies to control single-phase uninterruptible power supply (UPS) inverters, they suffer from some drawbacks, the main being complexity. This paper proposes a simple dual-loop controller for the single-phase UPS inverter with the LC filter. The suggested control scheme uses the capacitor current as the feedback signal in the inner current loop. No fictitious phase generation or reference frame transformations are required, and simple proportional gains are employed as both voltage and current regulators. A feedforward of the derivative of the output voltage is also proposed, which significantly improves the performance of the closed loop control system. Then, based on the model of the inverter with the proposed control strategy, a simple and systematic design procedure is presented. Finally, the theoretical achievements are supported by extensive simulations.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2014, 62, 2; 367-373
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A repeatability study of artificial neural network predictions in flow stress model development for a magnesium alloy
    Autorzy:
    Siewior, Hubert
    Madej, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/29520089.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    flow stress
    artificial neural networks
    feedforward
    recursive
    Opis:
    This work is devoted to an evaluation of the capabilities of artificial neural networks (ANN) in terms of developing a flow stress model for magnesium ZE20. The learning procedure is based on experimental flow-stress data following inverse analysis. Two types of artificial neural networks are investigated: a simple feedforward version and a recursive one. Issues related to the quality of input data and the size of the training dataset are presented and discussed. The work confirms the general ability of feedforward neural networks in flow stress data predictions. It also highlights that slightly better quality predictions are obtained using recursive neural networks.
    Źródło:
    Computer Methods in Materials Science; 2021, 21, 4; 209-218
    2720-4081
    2720-3948
    Pojawia się w:
    Computer Methods in Materials Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Decision making support system for managing advertisers by ad fraud detection
    Autorzy:
    Gabryel, Marcin
    Scherer, Magdalena M.
    Sułkowski, Łukasz
    Damaševičius, Robertas
    Powiązania:
    https://bibliotekanauki.pl/articles/2031082.pdf
    Data publikacji:
    2021
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    lead management
    feedforward neural networks
    embedding
    online marketing
    Opis:
    Efficient lead management allows substantially enhancing online channel marketing programs. In the paper, we classify website traffic into human- and bot-origin ones. We use feedforward neural networks with embedding layers. Moreover, we use one-hot encoding for categorical data. The data of mouse clicks come from seven large retail stores and the data of lead classification from three financial institutions. The data are collected by a JavaScript code embedded into HTML pages. The three proposed models achieved relatively high accuracy in detecting artificially generated traffic.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 4; 331--339
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Convergence Analysis of Multilayer Feedforward Networks Trained with Penalty Terms: A review
    Autorzy:
    Wang, J.
    Yang, G.
    Liu, S.
    Zurada, J. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/108639.pdf
    Data publikacji:
    2015
    Wydawca:
    Społeczna Akademia Nauk w Łodzi
    Tematy:
    Gradient
    feedforward neural networks
    generalization
    penalty
    convergence
    pruning algorithms
    Opis:
    Gradient descent method is one of the popular methods to train feedforward neural networks. Batch and incremental modes are the two most common methods to practically implement the gradient-based training for such networks. Furthermore, since generalization is an important property and quality criterion of a trained network, pruning algorithms with the addition of regularization terms have been widely used as an efficient way to achieve good generalization. In this paper, we review the convergence property and other performance aspects of recently researched training approaches based on different penalization terms. In addition, we show the smoothing approximation tricks when the penalty term is non-differentiable at origin.
    Źródło:
    Journal of Applied Computer Science Methods; 2015, 7 No. 2; 89-103
    1689-9636
    Pojawia się w:
    Journal of Applied Computer Science Methods
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Repetitive neurocontroller with disturbance feedforward path active in the pass-to-pass direction for a VSI inverter with an output LC filter
    Autorzy:
    Ufnalski, B.
    Grzesiak, L. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/200017.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    repetitive control
    feedforward neural network
    dynamic optimization problem
    repetitive disturbance rejection
    voltage source inverter
    disturbance dual feedforward path
    sterowanie powtarzalne
    sieci neuronowe
    problem optymalizacji dynamicznej
    przetwornica napięcia
    odrzucanie zakłóceń
    Opis:
    An enhancement to the previously developed repetitive neurocontroller (RNC) is discussed and investigated in the paper. Originally, the time-base generator (TBG) has been used to produce the only input signal for the neural approximator. The resulting search space makes the dynamic optimization problem (DOP) of shaping the control signal solvable with the help of a function approximator such as the feed-forward neural network (FFNN). The plant under consideration, i.e. a constant-amplitude constant-frequency voltage-source inverter (CACF VSI) with an output LC filter, is assumed to be equipped with the disturbance load current sensor to enable implementation of the disturbance feed-forward (pDFF) path as a part of the non-repetitive subsystem acting in the along the pass p-direction. An investigation has been undertaken to explore potential benefits of using this signal also as an additional input for the RNC to augment the approximation space and potentially enhance the convergence rate of the real-time search process. It is numerically demonstrated in the paper that the disturbance feed-forward path active in the pass-to-pass k-direction (kDFF) improves the dynamics of the repetitive part as well indeed.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 1; 115-125
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bilateral teleoperation system for a mini crane
    Autorzy:
    Herbin, Paweł
    Woźniak, Marcin
    Powiązania:
    https://bibliotekanauki.pl/articles/135104.pdf
    Data publikacji:
    2019
    Wydawca:
    Akademia Morska w Szczecinie. Wydawnictwo AMSz
    Tematy:
    human robot interface
    machine control
    mechatronic system
    exoskeleton
    hri
    hydraulic crane
    feedforward control
    Opis:
    In this paper, two automatic mini-crane control systems have been compared; utilizing feedback as well as both feedback and feedforward structures. The proposed control systems were implemented in a Master-Slave system to provide intuitive control for a mini-crane by human muscles. The control systems that have been designed were tested on constructions with similar structures i.e. an upper limb exoskeleton and a mini-crane with two joints, but using different actuation systems. The mini-crane had hydraulic actuators, whereas the exoskeleton was equipped with electrical actuators.
    Źródło:
    Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2019, 57 (129); 63-69
    1733-8670
    2392-0378
    Pojawia się w:
    Zeszyty Naukowe Akademii Morskiej w Szczecinie
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Forecasting economic and financial indicators by supply of deep and recovery neural networks
    Autorzy:
    Boyko, N.
    Ivanets, A.
    Bosik, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/411261.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Oddział w Lublinie PAN
    Tematy:
    neural network
    deep
    recurrent
    activation function
    feedforward
    neuron
    hidden layer
    stock price prediction
    Opis:
    This paper studies the potential of the application of the Recurrent Neural Networks, as well as the Deep Neural Networks in the field of the finances and trading. In particular, their use in the stock price predicting software. The concepts of the RNNs and DNNs are provided and explained thoroughly. Both techniques RNNs and DNNs are utilized in the implementation of the stock price predicting software. Two separate versions of the software are created in order to demonstrate the main differences between the algorithms, as well as to determine the best of the two. Each version is thoroughly examined. The comparison of each of the algorithms is performed and highlighted. Examples of the implementations of the software, utilizing each of the algorithms on big volumes of stock data, for stock price prediction are provided. The article summarizes the concept of stock price prediction backed by the popular machine learning algorithms and its application in the nowadays world.
    Źródło:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2018, 7, 2; 3-8
    2084-5715
    Pojawia się w:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Earplug Actuator Selection for a Miniature Personal Active Hearing Protection System
    Autorzy:
    Pawełczyk, M.
    Latos, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/178052.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    active noise control
    fixed-parameter control
    high-level noise
    nonstationary noise
    feedforward control
    earplug
    hearing protection
    Opis:
    There are many industrial environments which are exposed to a high-level noise. It is necessary to protect people from the noise. Most of the time, the consumer requires a miniature version of a noise canceller to satisfy the internal working place requirements. Very important thing is to select the most appropriate personal hearing protection device, for example an earplug. It should guarantee high passive noise attenuation and allow for secondary sound generation in case of active control. In many cases the noise is nonstationary. For instance, some of the noisy devices are switched on and off, speed of some rotors or fans changes, etc. To avoid any severe transient acoustic effects due to potential convergence problems of adaptive systems, a fixed-parameter approach to control is appreciated. If the noise were stationary, it would be possible to design an optimal control filter minimising variance of the signal being the effect of the acoustic noise and the secondary sound interference. Because of noise nonstationarity for most applications, the idea of generalised disturbance defined by a frequency window of different types has been developed by the authors and announced in previous publications. The aim of this paper is to apply such an approach to different earplugs and verify its noise reduction properties. Simulation experiments are conducted based on real world measurements performed using the G.R.A.S. artificial head equipped with an artificial mechanical ear, and the noise recorded in a power plant.
    Źródło:
    Archives of Acoustics; 2010, 35, 2; 213-222
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Neuromechanical control in submaximal drop jumps: The effects of volitional effort demands and drop height magnitude on soleus muscle activation
    Autorzy:
    Mrdakovic, V.
    Pazin, N.
    Vulovic, R.
    Filipovic, N.
    Ilic, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/307166.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    elektromiografia
    sprzężenie zwrotne
    staw skokowy
    biomechanika
    electromyography
    stretch-shortening cycle
    feedback control
    pre activation
    feedforward control
    ankle biomechanics
    Opis:
    The purpose of this study was to investigate soleus muscle activation during different phases of drop jump performed at submaximal levels of volitional effort and drop height magnitude. Methods: Fifteen professional volleyball players with minimum of eight years of experience in jumping activities participated in the study. Experimental protocol involved executing submaximal drop jumps at three levels of volitional effort (i.e., 65, 80 and 95% of the maximal height of jump). All submaximal drop jumps were done from three drop heights (20, 40 and 60 cm). The soleus muscle activation was monitored during four jump phases: pre-activation phase before touchdown, early contact phase upon touchdown, early and late push-off phase. Results: The results indicate that volitional effort level did not change the muscle activation during pre activation and early contact phase, but only in early and late push-off phase ( p ≤ 0.05). Conversely, it was observed that muscle activation during all phases of drop jump was adapted to the increased intensity of the external load caused by increasing of drop height magnitude ( p ≤ 0.01). Conclusions: The findings of the present study suggested that soleus muscle activation has selective responses to internal load (i.e., volitional effort level) and external load (i.e., drop height magnitude) intensities when drop jump is executing with submaximal effort.
    Źródło:
    Acta of Bioengineering and Biomechanics; 2018, 20, 4; 101-111
    1509-409X
    2450-6303
    Pojawia się w:
    Acta of Bioengineering and Biomechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Quiet Zone for the patient in an Ambulance : Active Noise Control Technology for Siren Noise Reduction
    Autorzy:
    Sharma, M. K.
    Vig, R.
    Pal, R.
    Shantharam, V.
    Powiązania:
    https://bibliotekanauki.pl/articles/177099.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    active noise control
    ANC
    virtual sensing technique
    ambulance siren noise
    zone of silence
    feedforward ANC
    virtual ANC
    Opis:
    This paper proposes an active noise control (ANC) application to attenuate siren noise for the patient lying inside ambulance with no sound proofing. From the point of cost effectiveness, a local ANC system based on feedforward scheme is considered. Further, to handle the limitation of limited Zone of Silence (ZoS), the ANC based on virtual sensing is explored. The simulations are done in MATLAB for the recorded ambulance siren noise signal. The results indicate that ANC can be an effective solution for creating a silent environment for the patient.
    Źródło:
    Archives of Acoustics; 2018, 43, 2; 275-281
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using artificial neural networks to predict the reference evapotranspiration
    Autorzy:
    Abo El-Magd, Amal
    Baraka, Shaimaa M.
    Eid, Samir F.M.
    Powiązania:
    https://bibliotekanauki.pl/articles/27312640.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    climate data
    ETo calculator
    feedforward artificial neural networks
    Penman-Monteith method
    reference evaporation
    root mean square error
    Opis:
    Artificial neural network models (ANNs) were used in this study to predict reference evapotranspiration (ETo) using climatic data from the meteorological station at the test station in Kafr El-Sheikh Governorate as inputs and reference evaporation values computed using the Penman-Monteith (PM) equation. These datasets were used to train and test seven different ANN models that included different combinations of the five diurnal meteorological variables used in this study, namely, maximum and minimum air temperature (Tmax and Tmin ), dew point temperature (Tdw), wind speed (u), and precipitation (P), how well artificial neural networks could predict ETo values. A feed-forward multi-layer artificial neural network was used as the optimization algorithm. Using the tansig transfer function, the final architected has a 6-5-1 structure with 6 neurons in the input layer, 5 neurons in the hidden layer, and 1 neuron in the output layer that corresponds to the reference evapotranspiration. The root mean square error (RMSE) of 0.1295 mm∙day -1 and the correlation coefficient (r) of 0.996 are estimated by artificial neural network ETo models. When fewer inputs are used, ETo values are affected. When three separate variables were employed, the RMSE test values were 0.379 and 0.411 mm∙day -1 and r values of 0.971 and 0.966, respectively, and when two input variables were used, the RMSE test was 0.595 mm∙day -1 and the r of 0.927. The study found that including the time indicator as an input to all groups increases the prediction of ETo values significantly, and that including the rain factor has no effect on network performance. Then, using the Penman-Monteith method to estimate the missing variables by using the ETo calculator the normalised root mean squared error (NRMSE) reached about 30% to predict ETo if all data except temperature is calculated, while the NRMSE reached about of 13.6% when used ANN to predict ETo using variables of temperature only.
    Źródło:
    Journal of Water and Land Development; 2023, 57; 1--8
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Feedforward neural networks and the forecasting of multi-sectional demand for telecom services: a comparative study of effectiveness for hourly data
    Jednokierunkowe sieci neuronowe w prognozowaniu wieloprzekrojowego popytu na usługi telefoniczne – porównawcze badania efektywności dla danych godzinowych
    Autorzy:
    Kaczmarczyk, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/2117264.pdf
    Data publikacji:
    2020
    Wydawca:
    Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
    Tematy:
    Prediction System
    feedforward neural network
    regressive-neural model
    forecasting
    jednokierunkowa sieć neuronowa
    model regresyjno-neuronowy
    prognozowanie
    system prognostyczny
    Opis:
    The presented research focuses on the construction of a model to effectively forecast demand for connection services – it is thus relevant to the Prediction System (PS) of telecom operators. The article contains results of comparative studies regarding the effectiveness of neural network models and regressive-neural (integrated) models, in terms of their short-term forecasting abilities for multi-sectional demand of telecom services. The feedforward neural network was used as the neural network model. A regressive-neural model was constructed by fusing the dichotomous linear regression of multi-sectional demand and the feedforward neural network that was used to model the residuals of the regression model (i.e. the residual variability). The response variable was the hourly counted seconds of outgoing calls within the framework of the selected operator network. The calls were analysed within: type of 24 hours (e.g. weekday/weekend), connection categories, and subscriber groups. For both compared models 35 explanatory variables were specified and used in the estimation process. The results show that the regressive-neural model is characterised by higher approximation and predictive capabilities than the non-integrated neural model.
    Zaprezentowane wyniki badań są związane z systemem prognostycznym przeznaczonym dla operatorów telekomunikacyjnych, ponieważ są skoncentrowane na sposobie konstrukcji modelu do efektywnego prognozowania popytu na usługi połączeniowe. Artykuł zawiera wyniki porównawczych badań efektywności modelu sieci neuronowej i modelu regresyjno-neuronowego (zintegrowanego) w zakresie krótkookresowego prognozowania zapotrzebowania na usługi telefoniczne. Jako model sieci neuronowej zastosowany został model sieci jednokierunkowej. Model regresyjno-neuronowy został zbudowany na podstawie połączenia dychotomicznej regresji liniowej wieloprzekrojowego popytu i jednokierunkowej sieci neuronowej, która służyła do modelowania reszt modelu regresji (tj. pozostałej zmienności). Zmienną objaśnianą były sumowane co godzinę liczby sekund rozmów wychodzących z sieci wybranego operatora. Połączenia telefoniczne były analizowane pod względem: typów doby, kategorii połączeń i grup abonentów. Wyszczególniono 35 zmiennych objaśniających, które wykorzystano w procesie estymacji obu porównywanych modeli. Stwierdzono, że model regresyjno-neuronowy charakteryzuje się większymi możliwościami aproksymacyjnymi i predykcyjnymi niż niezintegrowany model neuronowy.
    Źródło:
    Acta Scientiarum Polonorum. Oeconomia; 2020, 19, 3; 13-25
    1644-0757
    Pojawia się w:
    Acta Scientiarum Polonorum. Oeconomia
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimal design of model following control with genetic algorithm
    Autorzy:
    Zhang, X.
    Yamane, Y.
    Powiązania:
    https://bibliotekanauki.pl/articles/205732.pdf
    Data publikacji:
    2001
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    algorytm genetyczny
    model optymalny
    sprzężenie do przodu
    sprzężenie zwrotne
    feedback
    feedforward
    genetic algorithm
    model following control (MFC)
    optimal design
    Opis:
    This paper presents a genetic algorithm for the optimal design of model following control in which there are nonlinear disturbance and unceratin parameters, where the output is regulated to follow the output of reference model. The effectiveness of the proposed algorithm is illustrated by numerical examples.
    Źródło:
    Control and Cybernetics; 2001, 30, 1; 71-79
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optymalne sterowanie temperaturą i stężeniem dwutlenku węgla w wybranym procesie klimatycznym szklarni
    Optimal control of temperature and carbon dioxide concentration in selected greenhouse climate process
    Autorzy:
    Stankiewicz, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/287823.pdf
    Data publikacji:
    2009
    Wydawca:
    Polskie Towarzystwo Inżynierii Rolniczej
    Tematy:
    sterowanie
    klimat
    szklarnia
    model matematyczny
    sprzężenie zwrotne
    sprzężenie "wprzód"
    greenhouse climate control
    feedback control
    feedforward control
    time-multiplied performance index
    Opis:
    W pracy rozważa się zadanie równoczesnego sterowania temperaturą powietrza i stężeniem dwutlenku węgla wewnątrz szklarni dla wybranego, znanego w literaturze, systemu klimatycznego szklarni. Sterowanie realizowane jest w systemie sterowania typu feedback-feedforward, który pozwala w torze sprzężenia "wprzód" skutecznie i szybko kompensować skutki szybkozmiennych deterministycznych zakłóceń, a w torze sprzężenia zwrotnego od stanu procesu zapewnia szybkie zanikanie błędu sterowania. Macierz regulatora dobrano optymalnie w sensie całkowego wskaźnika kwadratowego z mnożnikiem czasowym. Wyniki eksperymentów przeprowadzonych z wykorzystaniem programu Matlab/Simulink dowodzą skuteczności zastosowanej struktury i algorytmu sterowania.
    The control of the temperature and carbon dioxide concentration inside the greenhouse is an important tool to control crop growth both in a qualitative as well as in a quantitative sense in view of the horticultural practice of modern greenhouses. The simulation experiments were conducted for simultaneous control of the temperature and carbon dioxide concentration for the known in the literature example of the production of a lettuce crop by the use of the Simulink toolbox of Matlab. The effectiveness of the model based feedback-feedforward control system is demonstrated for the state variables stabilization on piecewise constant user-desired or computed by the upper optimization level set-points.
    Źródło:
    Inżynieria Rolnicza; 2009, R. 13, nr 9, 9; 273-281
    1429-7264
    Pojawia się w:
    Inżynieria Rolnicza
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Eco-Humanism and Popular System Dynamics as Preconditions for Sustainable Development
    Eko-humanizm i systemy dynamiczne jako warunki wstępne dla zrównoważonego rozwoju
    Autorzy:
    Michnowski, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/371727.pdf
    Data publikacji:
    2008
    Wydawca:
    Polska Akademia Nauk. Komitet Człowiek i Środowisko PAN
    Tematy:
    global crisis
    sustainable development
    feedback
    feedforward
    economic planning
    ecosystem management
    social change
    political science
    interdisciplinary research
    system dynamics
    dynamic monitoring
    Opis:
    This article is parallelly published by Luis T. Gutierrez in the Solidarity, Sustainability, and Non-Violence Research Newsletter – (http://pelicanweb.org/solisustv03n11michnowski.html). This article is an overview of a book by the author: "Vision of sustainable development society – future of the world from cyberneticist perspective” (in Polish), published by Polish Academy of Sciences, Committee for Futures Studies "Poland 2000 Plus", Warsaw Poland 2006 (Michnowski, 2006).. This book contains my conclusions from - System of Life reality conceptual model based - systems analysis of global crisis essence and world society sustainable development, especially information, conditions creating. The main thesis of mine is: to avoid global catastrophe, NO LIMITS TO WISDOM BASED GROWTH AND SUSTAINABLE DEVELOPMENT OF THE HUMANKIND.
    Źródło:
    Problemy Ekorozwoju; 2008, 3, 2; 31-50
    1895-6912
    Pojawia się w:
    Problemy Ekorozwoju
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Feedforward feedback iterative learning control method for the multilayer boundaries of oversaturated intersections based on the macroscopic fundamental diagram.
    Autorzy:
    Lin, Xiaohui
    Xu, Jianmin
    Powiązania:
    https://bibliotekanauki.pl/articles/224037.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    traffic engineering
    oversaturated intersection
    multilayer boundary
    macroscopic fundamental diagram
    feedforward feedback
    iterative control
    inżynieria ruchu
    przesycone skrzyżowanie
    granica wielowarstwowa
    makroskopowy diagram fundamentalny
    sprzężenie zwrotne
    Opis:
    The feedback control based on the model and method of iterative learning control, which in turn is based on the macroscopic fundamental diagram (MFD), mostly belongs to the classification of single-layer boundary control method. However, the feedback control method has the problem of time delay. Therefore, a feed forward feedback iterative learning control (FFILC) method based on MFD of the multi-layer boundary of single-area oversaturated intersections is proposed. The FFILC method can improve the effectiveness of boundary control and avoid the time-delay problem of feedback control. Firstly, MFD theory is used to determine the MFD of the control area; the congestion zone and the transition zone of the control area are identified; and the two-layer boundary of the control area is determined. Then, the FFILC controllers are established at the two-layer boundary of the control area. When the control area enters into a congestion state, the control ratio of traffic flow in and out of the two-layer boundary is adjusted. The cumulative number of vehicles in the control area continues to approach the optimal cumulative number of vehicles, and it maintains high traffic efficiency with high flow rates. Finally, The actual road network is taken as the experimental area, and the road network simulation platform is built. The controller of the feedforward iterative learning control (FILC) is selected as the comparative controller and used to analyse the iterative effect of FFILC. Improvements in the use of traffic signal control indicators for the control area are analysed after the implementation of the FFILC method. Results show that the FFILC method considerably reduces the number of iterations, and it can effectively improve convergence speed and the use of traffic signal evaluation indicators for the control area.
    Źródło:
    Archives of Transport; 2020, 53, 1; 67-87
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    O optymalnym sterowaniu temperaturą i stężeniem dwutlenku węgla w szklarni
    On the optimal control of temperature and CO2 concentration in greenhouse
    Autorzy:
    Stankiewicz, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/287078.pdf
    Data publikacji:
    2009
    Wydawca:
    Polskie Towarzystwo Inżynierii Rolniczej
    Tematy:
    sterowanie
    klimat
    szklarnia
    model matematyczny
    sprzężenie zwrotne
    sprzężenie "wprzód"
    greenhouse climate control
    model-based control
    feedback control
    feedforward control
    time-multiplied performance index
    Opis:
    Systemy sterowania klimatem we współczesnych szklarniach to złożone struktury wykorzystujące model matematyczny sterowanego procesu i nowoczesne koncepcje sterowania. W pracy rozważa się zadanie równoczesnej stabilizacji temperatury powietrza i stężenie dwutlenku węgla wewnątrz szklarni przy odcinkami stałych wartościach zadanych. Zaproponowano nowy system sterowania typu feedback-feedforward, który pozwala w torze sprzężenia "wprzód" skutecznie i szybko niwelować skutki szybkozmiennych zakłóceń, a w torze sprzężenia zwrotnego od stanu procesu zapewnia szybkie zanikanie błędu sterowania. Macierz regulatora dobrano optymalnie w sensie wskaźnika z mnożnikiem czasowym.
    The optimal control of greenhouse climate has received considerable attention in agricultural engineering research. In this paper a new feedback-feedforward control system is proposed for the state variables stabilization on piecewise constant user-desired or computed by the upper level set-points for temperature and CO2 concentration. The proposed control structure consists of two main parts: a model based feedforward compensation of external disturbances and the model based optimal feedback simultaneous control of the greenhouse temperature and CO2 concentration. The applied decomposition is able to deal with rapidly fluctuating deterministic external inputs or disturbances acting on the system by feedforward static compensation and guarantee the fast decay of the control error due to the static state feedback with constant gain matrix optimal in the sense of timemultiplied quadratic index. In a forthcoming paper, the simulation experiments will be conducted for the known in the literature example of the production of a lettuce crop by the use of the Simulink toolbox of Matlab in order to demonstrate the effectiveness of the control system proposed.
    Źródło:
    Inżynieria Rolnicza; 2009, R. 13, nr 8, 8; 189-198
    1429-7264
    Pojawia się w:
    Inżynieria Rolnicza
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robust fractional adaptive control based on the strictly positive realness condition
    Autorzy:
    Ladaci, S.
    Charef, A.
    Loiseau, J. J.
    Powiązania:
    https://bibliotekanauki.pl/articles/907854.pdf
    Data publikacji:
    2009
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    sterowanie odporne
    sterowanie adaptacyjne
    sprzężenie do przodu
    rachunek ułamkowy
    positive realness
    robust control
    adaptive control
    fractional adaptive control
    model reference adaptive control
    feedforward
    fractional calculus
    Opis:
    This paper presents a new approach to robust adaptive control, using fractional order systems as parallel feedforward in the adaptation loop. The problem is that adaptive control systems may diverge when confronted with finite sensor and actuator dynamics, or with parasitic disturbances. One of the classical robust adaptive control solutions to these problems makes use of parallel feedforward and simplified adaptive controllers based on the concept of positive realness. The proposed control scheme is based on the Almost Strictly Positive Realness (ASPR) property of the plant. We show that this condition implies also robust stability in the case of fractional order controllers. An application to Model Reference Adaptive Control (MRAC) with a fractional order adaptation rule is provided with an implementable algorithm. A simulation example of a SISO robust adaptive control system illustrates the advantages of the proposed method in the presence of disturbances and noise.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2009, 19, 1; 69-76
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Stabilising solutions to a class of nonlinear optimal state tracking problems using radial basis function networks
    Autorzy:
    Ahmida, Z.
    Charef, A.
    Becerra, V. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/908523.pdf
    Data publikacji:
    2005
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    system nieliniowy
    sterowanie optymalne
    radialna funkcja bazowa
    sieć neuronowa
    regulacja predykcyjna
    sterowanie wyprzedzające
    nonlinear systems
    optimal control
    radial basis functions
    neural networks
    predictive control
    feedforward control
    Opis:
    A controller architecture for nonlinear systems described by Gaussian RBF neural networks is proposed. The controller is a stabilising solution to a class of nonlinear optimal state tracking problems and consists of a combination of a state feedback stabilising regulator and a feedforward neuro-controller. The state feedback stabilising regulator is computed online by transforming the tracking problem into a more manageable regulation one, which is solved within the framework of a nonlinear predictive control strategy with guaranteed stability. The feedforward neuro-controller has been designed using the concept of inverse mapping. The proposed control scheme is demonstrated on a simulated single-link robotic manipulator.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2005, 15, 3; 369-381
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Forward and inverse kinematics solution of a robotic manipulator using a multilayer feedforward neural network
    Autorzy:
    Sharkawy, Abdel-Nasser
    Powiązania:
    https://bibliotekanauki.pl/articles/2201647.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Koszalińska. Wydawnictwo Uczelniane
    Tematy:
    multilayer neural network
    feedforward neural network
    forward kinematics
    inverse kinematics
    2-DOF planar robot
    Levenberg-Marquardt algorithm
    generated data
    sieci neuronowe
    sieci neuronowe jednokierunkowe
    sieci neuronowe wielowarstwowe
    kinematyka prosta
    kinematyka odwrotna
    algorytm Levenberga-Marquardta
    generowanie danych
    Opis:
    In this paper, a multilayer feedforward neural network (MLFFNN) is proposed for solving the problem of the forward and inverse kinematics of a robotic manipulator. For the forward kinematics solution, two cases are presented. The first case is that one MLFFNN is designed and trained to find solely the position of the robot end-effector. In the second case, another MLFFNN is designed and trained to find both the position and the orientation of the robot end-effector. Both MLFFNNs are designed considering the joints’ positions as the inputs. For the inverse kinematics solution, a MLFFNN is designed and trained to find the joints’ positions considering the position and the orientation of the robot end-effector as the inputs. For training any of the proposed MLFFNNs, data is generated in MATLAB using two different cases. The first case is that data is generated assuming an incremental motion of the robot’s joints, whereas the second case is that data is obtained with a real robot considering a sinusoidal joint motion. The MLFFNN training is executed using the Levenberg-Marquardt algorithm. This method is designed to be used and generalized to any DOF manipulator, particularly more complex robots such as 6-DOF and 7-DOF robots. However, for simplicity, this is applied in this paper using a 2-DOF planar robot. The results show that the approximation error between the desired output and the estimated one by the MLFFNN is very low and it is approximately equal to zero. In other words, the MLFFNN is efficient enough to solve the problem of the forward and inverse kinematics, regardless of the joint motion type.
    Źródło:
    Journal of Mechanical and Energy Engineering; 2022, 6, 2; 1--17
    2544-0780
    2544-1671
    Pojawia się w:
    Journal of Mechanical and Energy Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Dynamic fire risk prevention strategy in underground coal gasification processes by means of artificial neural networks
    Dynamiczna strategia zapobiegania ryzyku pożarowemu z użyciem sztucznych sieci neuronowych w procesach podziemnego zgazowania węgla
    Autorzy:
    Krzemień, Alicja
    Powiązania:
    https://bibliotekanauki.pl/articles/218921.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    dynamiczna strategia zapobiegania ryzyku
    prewencja ryzyka pożarowego
    podziemne zgazowanie węgla (PZW)
    dynamic alarm strategy
    fire risk prevention
    Generalized Regression Neural Network
    Multi-Layer Feedforward Networks (MLFN)
    Multivariate Adaptative Regression Splines (MARS)
    underground coal gasification (UCG)
    Opis:
    Based on data collected during an UCG pilot-scale experiment that took place during 2014 at Wieczorek mine, an active mine located in Upper Silesia (Poland), this research focuses on developing a dynamic fire risk prevention strategy addressing underground coal gasification processes (UCG) within active mines, preventing economic and physical losses derived from fires. To achieve this goal, the forecasting performance of two different kinds of artificial neural network models (generalized regression and multi-layer feedforward) are studied, in order to forecast the syngas temperature at the georeactor outlet with one hour of anticipation, thus giving enough time to UCG operators to adjust the amount and characteristics of the gasifying agents if necessary. The same model could be used to avoid undesired drops in the syngas temperature, as low temperature increases precipitation of contaminants reducing the inner diameter of the return pipeline. As a consequence the whole process of UGC might be stopped. Moreover, it could allow maintaining a high temperature that will lead to an increased efficiency, as UCG is a very exothermic process. Results of this research were compared with the ones obtained by means of Multivariate Adaptative Regression Splines (MARS), a non-parametric regression technique able to model non-linearities that cannot be adequately modelled using other regression methods. Syngas temperature forecast with one hour of anticipation at the georeactor outlet was achieved successfully, and conclusions clearly state that generalized regression neural networks (GRNN) achieve better forecasts than multi-layer feedforward networks (MLFN) and MARS models.
    Przedstawione w niniejszej pracy badania koncentrują się na opracowaniu dynamicznej strategii zapobiegania ryzyku pożarowemu w procesach podziemnego zgazowania węgla (PZW) w czynnych kopalniach. Celem badań jest zapobieganie ekonomicznym i fizycznym stratom wynikającym z pożarów. W pracy wykorzystano dane zebrane podczas pilotowego eksperymentu podziemnego zgazowania węgla, który odbył się w 2014 r. w czynnej Kopalni Węgla Kamiennego „Wieczorek”, zlokalizowanej na Górnym Śląsku. W artykule przeanalizowano działanie dwóch różnych modeli sztucznych sieci neuronowych, tj. sieci neuronowych realizujących uogólnione regresje GRNN oraz wielowarstwowych sieci perceptronowych MLFN, w celu prognozowania temperatury gazu syntezowego na wyjściu z georeaktora z godzinnym wyprzedzeniem. Informacja na temat temperatury na godzinę „do przodu” daje wystarczająco dużo czasu operatorowi procesu PZW na dostosowanie ilości i właściwości czynników zgazowujących do zaistniałej sytuacji. Ten sam model można zastosować do uniknięcia niepożądanych spadków temperatury gazu syntezowego. Niska temperatura gazu sprzyja wytrącaniu się osadu (substancji smolistych), powodując zmniejszanie średnicy rurociągu odbioru gazu, co w konsekwencji może prowadzić do całkowitego zatrzymania procesu zgazowania. Model pozwala również na utrzymanie wysokiej temperatury, która prowadzi do zwiększonej wydajności procesu PZW, szczególnie biorąc pod uwagę, że PZW jest procesem bardzo egzotermicznym. Wyniki zrealizowanych badań porównano z rezultatami uzyskanymi za pomocą modelu MARS – nieparametrycznej metody regresji zdolnej do modelowania zależność nieliniowych, których nie można odpowiednio modelować przy użyciu innych metod regresji. Prognoza temperatury gazu na godzinę „do przodu” na wylocie georeaktora została osiągnięta z powodzeniem, a wnioski jasno pokazują, że sieci neuronowe realizujące uogólnione regresje (GRNN – Generalized Regression Neural Networks) osiągają lepsze rezultaty niż wielowarstwowe sieci jednokierunkowe (MLFN – Multi-Layer Feedforward Networks) i modele MARS (Multivariate Adaptative Regression Splines).
    Źródło:
    Archives of Mining Sciences; 2019, 64, 1; 3-19
    0860-7001
    Pojawia się w:
    Archives of Mining Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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