Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "neural network control" wg kryterium: Temat

  Lista filtrów
Wyrównaj
Wyświetlanie 1-15 z 51
Tytuł:
Comparison of the adaptive and neural network control for LWR 4+ manipulators: simulation study
Autorzy:
Woliński, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/140152.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
adaptive control
neural network control
redundant manipulator
Opis:
This paper deals with two control algorithms which utilize learning of their models’ parameters. An adaptive and artificial neural network control techniques are described and compared. Both control algorithms are implemented in MATLAB and Simulink environment, and they are used in the simulation of a postion control of the LWR 4+ manipulator subjected to unknown disturbances. The results, showing the better performance of the artificial neural network controller, are shown. Advantages and disadvantages of both controllers are discussed. The usefulness of the learning algorithms for the control of LWR 4+ robots is discussed. Preliminary experiments dealing with dynamic properties of the two LWR 4+ robots are reported.
Źródło:
Archive of Mechanical Engineering; 2020, LXVII, 1; 111-121
0004-0738
Pojawia się w:
Archive of Mechanical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural network control design considerations for the active damping of a smart beam
Autorzy:
Cupiał, P.
Łacny, Ł.
Powiązania:
https://bibliotekanauki.pl/articles/280299.pdf
Data publikacji:
2015
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
neural network control
smart structures
vibration damping
Opis:
In this study, possible options for the active damping of a smart beam with piezoelectric patches using neural network control algorithm, are presented. The algorithms used for the control are Neural Direct Inverse and Feedback Linearisation (NARMA-L2). Additionally, several possible modifications used for the purpose of improving the control, such as different values of control gain or sampling time of the training data, as well as step-wise control are tested.
Źródło:
Journal of Theoretical and Applied Mechanics; 2015, 53, 4; 767-774
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent control algorithm for ship dynamic positioning
Autorzy:
Meng, W.
Sheng, L. H.
Qing, M.
Rong, B. G.
Powiązania:
https://bibliotekanauki.pl/articles/229337.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
dynamic positioning
fuzzy control
neural network control
BP algorithm
Opis:
Ship motion in the sea is a complex nonlinear kinematics. The hydrodynamic coefficients of ship model are very difficult to accurately determine. Establishing accurate mathematical model of ship motion is difficult because of changing random factors in the marine environment. Aiming at seeking a method of control to realize ship positioning, intelligent control algorithms are adopt utilizing operator's experience. Fuzzy controller and the neural network controller are respectively designed. Through simulations and experiments, intelligent control algorithm can deal with the complex nonlinear motion, and has good robustness. The ship dynamic positioning system with neural network control has high positioning accuracy and performance.
Źródło:
Archives of Control Sciences; 2014, 24, 4; 479-497
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Identification of water treatment plant based on feedforward neural network
Autorzy:
Mohamed, A. F.
Radwa, H. Z.
Powiązania:
https://bibliotekanauki.pl/articles/971051.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
water treatment plant
coagulation process
PID
neural network control
Opis:
Coagulation process is the main process in conventional water treatment process sequence. It influences the following treatment process aspects: maintaining plant efficiency and increasing the quality of the produced water. This is accomplished by adding chemicals to raw water, such as alum sulphate. To secure the appropriate plant performance, a mathematical model is proposed in this paper for the coagulation unit, followed by the development of the control strategy. Classic PID and neural network based controller regulating the process are used. Tests were performed, based on the real data for water treatment, using MATLAB/SIMULINK. Simulation results showed better values for both settling time and overshoot in the case of using neural network based controller than PID.
Źródło:
Control and Cybernetics; 2017, 46, 3; 247-258
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural network simulation in running of acetic acid synthesis unit while start-up
Nejjroetevoe modelirovanie dlja upravlenija kolonnojj sinteza uksusnojj kisloty v period puska
Autorzy:
Porkuian, O.
Samojlova, Z.
Powiązania:
https://bibliotekanauki.pl/articles/792304.pdf
Data publikacji:
2013
Wydawca:
Komisja Motoryzacji i Energetyki Rolnictwa
Tematy:
neural network
artificial neural network
automated control system
acetic acid
MATLAB software
Źródło:
Teka Komisji Motoryzacji i Energetyki Rolnictwa; 2013, 13, 3
1641-7739
Pojawia się w:
Teka Komisji Motoryzacji i Energetyki Rolnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear Structural Acoustic Control with Shunt Circuit Governed by a Soft-Computing Algorithm
Autorzy:
Kurczyk, S.
Pawełczyk, M.
Powiązania:
https://bibliotekanauki.pl/articles/177699.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Active Noise Control
adaptive control
neural network
vibrating plate
Opis:
Noise control has gained a lot of attention recently. However, presence of nonlinearities in Signac paths for some applications can cause significant difficulties in the operation of control algorithms. In particular, this problem is common in structural noise control, which uses a piezoelectric shunt circuit. Not only vibrating structures may exhibit nonlinear characteristics, but also piezoelectric actuators. In this paper, active device casing is addressed. The objective is to minimize the noise coming out of the casing, by controlling vibration of its walls. The shunt technology is applied. The proposed control algorithm is based on algorithms from a group of soft computing. It is verified by means of simulations using data acquired from a real object.
Źródło:
Archives of Acoustics; 2018, 43, 3; 397-402
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Elman neural network for modeling and predictive control of delayed dynamic systems
Autorzy:
Wysocki, A.
Ławryńczuk, M.
Powiązania:
https://bibliotekanauki.pl/articles/229646.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
dynamic models
process control
model predictive control
neural networks
Elman neural network
delayed systems
Opis:
The objective of this paper is to present a modified structure and a training algorithm of the recurrent Elman neural network which makes it possible to explicitly take into account the time-delay of the process and a Model Predictive Control (MPC) algorithm for such a network. In MPC the predicted output trajectory is repeatedly linearized on-line along the future input trajectory, which leads to a quadratic optimization problem, nonlinear optimization is not necessary. A strongly nonlinear benchmark process (a simulated neutralization reactor) is considered to show advantages of the modified Elman neural network and the discussed MPC algorithm. The modified neural model is more precise and has a lower number of parameters in comparison with the classical Elman structure. The discussed MPC algorithm with on-line linearization gives similar trajectories as MPC with nonlinear optimization repeated at each sampling instant.
Źródło:
Archives of Control Sciences; 2016, 26, 1; 117-142
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Stabilizacja emisji NOx z pojedynczego palnika pyłowego z wykorzystaniem NPC i neuronowej metody estymacji parametrów spalania
Individual burner NOx emission stabilization with the use of NPC and neural method for estimation of combustion parameters
Autorzy:
Wójcik, W.
Smolarz, A.
Powiązania:
https://bibliotekanauki.pl/articles/152214.pdf
Data publikacji:
2007
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
low-emission burner
combustion
process control
neural network
Opis:
W kotłach energetycznych pracuje od kilkunastu do kilkudziesięciu palników Sterowanie na podstawie pomiarów uśrednionych lub opóźnionych (np. z analizatorów gazowych umieszczonych na kominie), jest często za mało efektywne. Wady tej nie miałaby regulacja pracy pojedynczego palnika, ale brak jest metody pomiaru jego parametrów spalania. W artykule opisana jest próba konstrukcji układu regulacyjnego stabilizującego emisję NOx z pojedynczego palnika pyłowego z wykorzystaniem regulatora predykcyjnego z neuronowym modelem procesu (NPC). Do estymacji emisji zostały użyte sieci neuronowe i sygnał ze światłowodowego układu monitorującego wybrane strefy płomienia w pojedynczym palniku opracowanego w Katedrze Elektroniki Politechniki Lubelskiej. W artykule zawarte są wyniki symulacji takiego układu regulacji.
There are even several tens of burners operating in a power boiler so control based on averaged and delayed measurements (e.g. from gas analyzers located in flue gas duct) often results ineffective. Control of individual burner would not have such disadvantage but there is a lack of method of measurement of its combustion parameters. The article describes attempt to build a control system stabilizing NOx emission of individual pulverized coal burner using the predictive controller with neural internal process model (NPC). In order to estimate the emission neural networks and signal from fiber optic system for flame monitoring, developed in Department of Electronics of Lublin University of Technology were used. The article includes the results of simulation tests of such control system.
Źródło:
Pomiary Automatyka Kontrola; 2007, R. 53, nr 11, 11; 20-23
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural network-PID controller for roll fin stabilizer
Autorzy:
Ghassemi, H.
Dadmarzi, F. H.
Ghadimi, P.
Ommani, B.
Powiązania:
https://bibliotekanauki.pl/articles/259283.pdf
Data publikacji:
2010
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
Fin stabilizer
neural network
PID control
restoring force
Opis:
Fin stabilizers are very effective devices for controlling the ship roll motion against external wave-generated moments. Lift forces due to flow around fin with an angle of attack produce anti - roll moment. Therefore control of attack angle plays important role in reducing roll of ships. This paper presents results of using a combined neural network and PID for roll control of ship with small draught. Numerical results are given of around-fin flow analysis with considering free surface effect modelled by neural network and imposed to controlling loop. Hydraulic machinery constraints are also considered in the modelling. The obtained results show good performance of the controller in reducing roll amplitude in random seas. The approach can be used for any irregular sea conditions.
Źródło:
Polish Maritime Research; 2010, 2; 23-28
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural Network based control of Robot Manipulator
Autorzy:
Ohri, Arnav
Salim, Salim
Powiązania:
https://bibliotekanauki.pl/articles/1075537.pdf
Data publikacji:
2019
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
RBF Neural Network
Robotic Manipulator
Sliding Mode Control
Opis:
This article proposes an RBFNN (Radial Basis Function Neural Network) and sliding mode based controller to manipulate the robot manipulator. The technique used has been based on a sliding mode control approach that can drive the system towards a sliding surface by Gaussian radial basis function neural network based tuned-controller.
Źródło:
World Scientific News; 2019, 121; 9-16
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Active Noise Control Algorithm Based on a Neural Network and Nonlinear Input-Output System Identification Model
Autorzy:
Krukowicz, T.
Powiązania:
https://bibliotekanauki.pl/articles/178040.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
active noise control
neural network
system identification
nonlinear phenomena
Opis:
The development of digital signal processors and the increase in their computing capabilities bring opportunities to employ algorithms with multiple variable parameters in active noise control systems. Of particular interest are the algorithms based on artificial neural networks. This paper presents an active noise control algorithm based on a neural network and a nonlinear input-output system identification model. The purpose of the algorithm is an active noise control system with a nonlinear primary path. The algorithm uses the NARMAX system identification model. The neural network employed in the proposed algorithm is a multilayer perceptron. The error backpropagation rule with adaptive learning rate is employed to update the weight of the neural network. The performance of the proposed algorithm has been tested by numerical simulations. Results for narrow-band input signals and nonlinear primary path are presented below.
Źródło:
Archives of Acoustics; 2010, 35, 2; 191-202
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptive control of autonomous underwater vehicle based on fuzzy neural network
Autorzy:
Qin, Z.
Gu, J.
Powiązania:
https://bibliotekanauki.pl/articles/384507.pdf
Data publikacji:
2010
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
autonomous underwater vehicle
fuzzy neural network
adaptive control
stability
Opis:
This paper presents an adaptive control method based on fuzzy neural network for Autonomous Underwater Vehicle (AUV). The Fuzzy Neural Network (FNN) could build the inverse model of AUV through on-line learning algorithm, which is free of fuzzy neural network structure knowledge and prior fuzzy inference rules. The adaptive controller for AUV based on FNN is proposed, and then the stability of the resulting AUV closed-loop control system is analyzed by Lyaponov stability theory. The validity of the proposed control method has been verified through computer simulation experiments.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 1; 104-111
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modified neural network based cascaded control for product composition of reactive distillation
Autorzy:
Sakhre, V.
Jain, S.
Sapkal, V. S.
Agarwal, D. P.
Powiązania:
https://bibliotekanauki.pl/articles/778231.pdf
Data publikacji:
2016
Wydawca:
Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
Tematy:
composition
inferential control
neural network
reactive distillation
soft sensor
Opis:
In this research work, neural network based single loop and cascaded control strategies, based on Feed Forward Neural Network trained with Back Propagation (FBPNN) algorithm is carried out to control the product composition of reactive distillation. The FBPNN is modified using the steepest descent method. This modification is suggested for optimization of error function. The weights connecting the input and hidden layer, hidden and output layer is optimized using steepest descent method which causes minimization of mean square error and hence improves the response of the system. FBPNN, as the inferential soft sensor is used for composition estimation of reactive distillation using temperature as a secondary process variable. The optimized temperature profile of the reactive distillation is selected as input to the neural network. Reboiler heat duty is selected as a manipulating variable in case of single loop control strategy while the bottom stage temperature T9 is selected as a manipulating variable for cascaded control strategy. It has been observed that modified FBPNN gives minimum mean square error. It has also been observed from the results that cascaded control structure gives improved dynamic response as compared to the single loop control strategy.
Źródło:
Polish Journal of Chemical Technology; 2016, 18, 2; 111-121
1509-8117
1899-4741
Pojawia się w:
Polish Journal of Chemical Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparison of Intelligent Control Methods for the Ore Jigging Process
Autorzy:
Kulakova, Yelena
Wójcik, Waldemar
Suleimenov, Batyrbek
Smolarz, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/1844513.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
neural network
ore jiggling
control algorithm
fuzzy logic
correlation
Opis:
Efficient control of the process of jigging ore of small and fine grain allows avoiding the loss of valuable material in production residual. Due to the multi-dimensionality and multi-connectivity of this enrichment process, classical control methods do not allow achieving the maximum technological indicators of enrichment. This paper proposes investigating intelligent algorithms for controlling the jigging process, which determine the key variables - the level of the natural «bed» and the ripple frequency of the jigging machine. Algorithms are developed using fuzzy logic, neural and hybrid networks. The adequacy of intelligent algorithms was evaluated using the following criteria: correlation of expert and model values (R); Root Mean Square Error (RMSE); Mean absolute percentage error (MAPE). To assess the adequacy of the obtained algorithms, a test sample of input variables, different from the training one, was compiled. As a consequence, we determined an algorithm that gives a minimal discrepancy between the calculated and experimental data.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 3; 529-534
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural Network Identifier of a Four-wheeled Mobile Robot Subject to Wheel Slip
Autorzy:
Hendzel, Z
Trojnacki, M.
Powiązania:
https://bibliotekanauki.pl/articles/384453.pdf
Data publikacji:
2014
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
mobile robot
tracking control
wheels’ slip
neural network
Lyapunov stability
Opis:
The paper presents a sequential neural network (NN) identification scheme for the four-wheeled mobile robot subject to wheel slip. The sequential identification scheme, different from conventional methods of optimization of a cost function, attempts to ensure stability of the overall system while the neural network learns the nonlinearities of the mobile robot. An on-line weight learning algorithm is developed to adjust the weights so that the identified model can adapt to variations of the characteristics and operating points in the four-wheeled mobile robot. The proposed identification system that can guarantee stability is derived from the Lyapunov stability theory. Computer simulations have been conducted to illustrate the performance of the proposed solution by a series of experiments on the emulator of the wheeled mobile robot.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2014, 8, 4; 24-30
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 51

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies