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Wyświetlanie 1-15 z 164
Tytuł:
Fuzzy and Neural Control of an Induction Motor
Autorzy:
Denai, M., A.
Attia, S. A.
Powiązania:
https://bibliotekanauki.pl/articles/908003.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
automatyka
fuzzy control
neural networks
induction motor
vector control
speed observer
Opis:
This paper presents some design approaches to hybrid control systems combining conventional control techniques with fuzzy logic and neural networks. Such a mixed implementation leads to a more effective control design with improved system performance and robustness. While conventional control allows different design objectives such as steady state and transient characteristics of the closed loop system to be specified, fuzzy logic and neural networks are integrated to overcome the problems with uncertainties in the plant parameters and structure encountered in the classical model-based design. Induction motors are characterised by complex, highly non-linear and time-varying dynamics and inaccessibility of some states and outputs for measurements, and hence can be considered as a challenging engineering problem. The advent of vector control techniques has partially solved induction motor control problems, because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Fuzzy logic and neural network-based controllers are considered as potential candidates for such an application. Three control approaches are developed and applied to adjust the speed of the drive system. The first control design combines the variable structure theory with the fuzzy logic concept. In the second approach neural networks are used in an internal model control structure. Finally, a fuzzy state feedback controller is developed based on the pole placement technique. A simulation study of these methods is presented. The effectiveness of these controllers is demonstrated for different operating conditions of the drive system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2002, 12, 2; 221-233
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural control of a robotic manipulator in contact with a flexible and uncertain environment
Autorzy:
Gierlak, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/2233648.pdf
Data publikacji:
2023
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
robotics
robot control
nonlinear control systems
Opis:
This article presents the synthesis of a neural motion control system of a robot caused by disturbances of constraints limiting the movement, which are the result of flexibility and disturbances of the contact surface. A synthesis of the control law is presented, in which the knowledge of the robot's dynamics and the parameters of a susceptible environment is not required. Moreover, the stability of the system is guaranteed in the case of an inaccurately known surface of the environment. This was achieved by introducing an additional module to the control law in directions normal to the surface of the environment. This additional term can be interpreted as the virtual viscotic resistance and spring force acting on the robot. This approach ensured the self-regulation of the robot’s interaction force with the compliant environment, limiting the impact of the geometrical inaccuracy of the environment.
Źródło:
Acta Mechanica et Automatica; 2023, 17, 3; 435--444
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Trajectory tracking of a wheeled mobile robot with uncertainties and disturbances: proposed adaptive neural control
Autorzy:
Martins, N. A.
Alencar, M.
Lombardi, W. C.
Bertol, D. W.
Pieri, E. R.
Filho, H. F.
Powiązania:
https://bibliotekanauki.pl/articles/971045.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
wheeled mobile robot
trajectory tracking
kinematic control
variable structure control
dynamic control
sliding mode theory
neural networks
Lyapunov theory
Opis:
This paper analyses a trajectory tracking control problem for a wheeled mobile robot, Rusing integration of a kinematic neural controller (KNC) and a torque neural controller (TNC), in which both the kinematic and dynamic models contain uncertainties and disturbances. The proposed adaptive neural controller (PANC) is composed of the KNC and the TNC and is designed with use of a modeling technique of Gaussian radial basis function neural networks (RBFNNs). The KNC is a variable structure controller, based on the sliding mode theory and is applied to compensate for the disturbances of the wheeled mobile robot kinematics. The TNC is an inertia-based controller composed of a dynamic neural controller (DNC) and a robust neural compensator (RNC) applied to compensate for the wheeled mobile robot dynamics, bounded unknown disturbances, and neural network modeling errors. To minimize the problems found in practical implementations of the classical variable structure controllers (VSC) and sliding mode controllers (SMC), and to eliminate the chattering phenomenon, the nonlinear and continuous KNC and RNC of the TNC are applied in lieu of the discontinuous components of the control signals that are present in classical forms. Additionally, the PANC neither requires the knowledge of the wheeled mobile robot kinematics and dynamics nor the timeconsuming training process. Stability analysis, convergence of the tracking errors to zero, and the learning algorithms for the weights are guaranteed based on the Lyapunov method. Simulation results are provided to demonstrate the effectiveness of the proposed approach.
Źródło:
Control and Cybernetics; 2015, 44, 1; 47-98
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sterowanie neuronowe robotem równoległym - projekt i implementacja
Neural control of a parallel robot - design and implementation
Autorzy:
Petko, M.
Powiązania:
https://bibliotekanauki.pl/articles/156675.pdf
Data publikacji:
2006
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
implementacja
projektowanie
sterowanie neuronowe robotem równoległym
neural control of parallel robot
implementation
project
Opis:
W artykule przedstawiono projekt i implementację sterownika neuronowe-go równoległego robota o trzech stopniach swobody, przeznaczonego do frezowania. Sterownik jest oparty na neuronowym modelu odwrotnej dynamiki manipulatora uczonego na danych zebranych przy zastosowaniu stabilizującego sterownika wykorzystującego strukturalny model anali-tyczny manipulatora. Po zrealizowaniu wirtualnego i szybkiego prototy-powania sterownik został zaimplementowany w układzie FPGA z wpro-gramowanym mikroprocesorem. Współbieżna implementacja sprzętowo-programowa umożliwiła badanie możliwych realizacji algorytmu.
The paper presents design and implementation of neural controller for 3-DOF parallel robot for milling. The controller is based on neural model of the inverse dynamics of the manipulator, trained on data collected with the use of a computed torque stabilizing controller. After successful virtual and fast prototyping, the controller was implemented in a FPGA with a soft-processor. Hardware-Software Co-design allowed for exploration of possible control algorithm realisations.
Źródło:
Pomiary Automatyka Kontrola; 2006, R. 52, nr 5, 5; 31-34
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptive neural network control of mechatronics objects
Autorzy:
Nemtsev, E.
Zukov, Y.
Powiązania:
https://bibliotekanauki.pl/articles/386408.pdf
Data publikacji:
2008
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
sieci neuronowe
symulacja komputerowa
obiekt mechatroniczny
neural network
computer simulation
mechatronics objects
Opis:
This paper presents an adaptive neural network approach to control of mechatronics objects. This approach is applied in adaptive control of DC motor in SISO-system and 3-DOF robot arm actuators in MIMO system. Results of computer simulation and comparison with other control techniques are introduced.
Źródło:
Acta Mechanica et Automatica; 2008, 2, 4; 81-85
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
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:
Neural model of the vehicle control system in a racing game. Part 2, Research experiments
Autorzy:
Bolesta, Arkadiusz
Tchórzewski, Jerzy
Powiązania:
https://bibliotekanauki.pl/articles/2175161.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
Godot Engine
MATLAB
Simulink environment
Neural control system
Perceptron Artificial Neural Networks
video games
Opis:
This article, which is a continuation of the article under the same main title and subtitle: part 1 Design and its implementation, includes the obtained results of research experiments with the use of a designed and implemented racing game. It uses a neural model of the vehicle motion control system on the racetrack in the form of a Perceptron Artificial Neural Network (ANN). In designing the movement of vehicles on the racetrack, the following were used, inter alia, Godot Engine and MATLAB and Simulink programming environment. The numerical data (14 input quantities and two output quantities) for ANN training were prepared with the use of semi-automatic measurement of the race track control points. This article shows, among others, the results of 10 selected research experiments, testing and simulation, confirming the correct functioning of both the computer game and the model of the neural control system. As a result of simulation tests, it turned out that the longest lap of the track in the conducted experiments lasted 4 minutes and 55 seconds, and the shortest - 10.47 seconds. In five minutes, the highest number of laps was 34, while the lowest numbers of laps were 1 and 5. In the course of the experiments it was noticed that under the same conditions the ANN learning outcomes are sometimes different.
Źródło:
Studia Informatica : systems and information technology; 2022, 1(26); 45--60
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Motor Control: Neural Models and Systems Theory
Autorzy:
Doya, K.
Kimura, H.
Miyamura, A.
Powiązania:
https://bibliotekanauki.pl/articles/908323.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
adaptacyjny układ sterowania
model wielokrotny
inverse model
adaptive control
cerebellum
reinforcement learning
basal ganglia
multiple models
Opis:
In this paper, we introduce several system theoretic problems brought forward by recent studies on neural models of motor control. We focus our attention on three topics: (i) the cerebellum and adaptive control, (ii) reinforcement learning and the basal ganglia, and (iii) modular control with multiple models. We discuss these subjects from both neuroscience and systems theory viewpoints with the aim of promoting interplay between the two research communities.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 1; 77-104
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combined system for off-line optimization and adaptive cutting force control
Autorzy:
Cus, F.
Balic, J.
Powiązania:
https://bibliotekanauki.pl/articles/100078.pdf
Data publikacji:
2010
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
manufacturing processes
adaptive cutting force control
milling simulator
neural control strateg
off-line optimization
Opis:
The choice of manufacturing processes is based on cost, time and precision. A remaining drawback of modern CNC systems is that the machining parameters, such as feed-rate, cutting speed and depth of cut, are still programmed off-line. The machining parameters are usually selected before machining accordin to programmer's experience and machining handbooks. To prevent damage and to avoid machining failure the operating conditions are usually set extremely conservative. As a result, many CNC systems are inefficient and run under the operating conditions that are far from optimal . Even if the machining parameters are optimised off-line by an optimisation algorithm they cannot be adjusted during the machining process. In this paper, a neural adaptiv controller is developed and some simulations and experiments with the neural control strategy are carried out. The results demonstrate the ability of the proposed system to effectively regulate peak forces for cutting conditions commonly encountered in end milling operations.
Źródło:
Journal of Machine Engineering; 2010, 10, 2; 25-35
1895-7595
2391-8071
Pojawia się w:
Journal of Machine 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:
Design of a multivariable neural controller for control of a nonlinear MIMO plant
Autorzy:
Bańka, S.
Dworak, P.
Jaroszewski, K.
Powiązania:
https://bibliotekanauki.pl/articles/330790.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
MIMO multivariable control system
nonlinear system
neural control
wielowymiarowy układ sterowania
układ nieliniowy
sterowanie neuronowe
Opis:
The paper presents the training problem of a set of neural nets to obtain a (gain-scheduling, adaptive) multivariable neural controller for control of a nonlinear MIMO dynamic process represented by a mathematical model of Low-Frequency (LF) motions of a drillship over the drilling point at the sea bottom. The designed neural controller contains a set of neural nets that determine values of its parameters chosen on the basis of two measured auxiliary signals. These are the ship’s current forward speed measured with respect to water and the systematically calculated difference between the course angle and the sea current (yaw angle). Four different methods for synthesis of multivariable modal controllers are used to obtain source data for training the neural controller with parameters reproduced by neural networks. Neural networks are designed on the basis of 3650 modal controllers obtained with the use of the pole placement technique after having linearized the model of LF motions made by the vessel at its nominal operating points in steady states that are dependent on the specified yaw angle and the sea current velocity. The final part of the paper includes simulation results of system operation with a neural controller along with conclusions and final remarks.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 357-369
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simulation and Analysis of Sintering Furnace Temperature Based on Fuzzy Neural Network Control
Autorzy:
Chaoxin, Zou
Rong, Li
Zhiping, Xie
Ming, Su
Jingshi, Zeng
Xu, Ji
Xiaoli, Ye
Ye, Wang
Powiązania:
https://bibliotekanauki.pl/articles/1837792.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fuzzy neural network
furnace
sintering
temperature control
PID
sieć neuronowa rozmyta
piec
spiekanie
kontrola temperatury
Opis:
Aiming at the problems of delay and couple in the sintering temperature control system of lithium batteries, a fuzzy neural network controller that can solve complex nonlinear temperature control is designed in this paper. The influence of heating voltage, air inlet speed and air inlet volume on the control of temperature of lithium battery sintering is analyzed, and a fuzzy control system by using MATLAB toolbox is established. And on this basis, a fuzzy neural network controller is designed, and then a PID control system and a fuzzy neural network control system are established through SIMULINK. The simulation shows that the response time of the fuzzy neural network control system compared with the PID control system is shortened by 24s, the system stability adjustment time is shortened by 160s, and the maximum overshoot is reduced by 6.1%. The research results show that the fuzzy neural network control system can not only realize the adjustment of lithium battery sintering temperature control faster, but also has strong adaptability, fault tolerance and anti-interference ability.
Źródło:
Archives of Foundry Engineering; 2021, 21, 1; 23-30
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simulation and Analysis of Sintering Furnace Temperature Based on Fuzzy Neural Network Control
Autorzy:
Chaoxin, Zou
Rong, Li
Zhiping, Xie
Ming, Su
Jingshi, Zeng
Xu, Ji
Xiaoli, Ye
Ye, Wang
Powiązania:
https://bibliotekanauki.pl/articles/1837849.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fuzzy neural network
furnace
sintering
temperature control
PID
sieć neuronowa rozmyta
piec
spiekanie
kontrola temperatury
Opis:
Aiming at the problems of delay and couple in the sintering temperature control system of lithium batteries, a fuzzy neural network controller that can solve complex nonlinear temperature control is designed in this paper. The influence of heating voltage, air inlet speed and air inlet volume on the control of temperature of lithium battery sintering is analyzed, and a fuzzy control system by using MATLAB toolbox is established. And on this basis, a fuzzy neural network controller is designed, and then a PID control system and a fuzzy neural network control system are established through SIMULINK. The simulation shows that the response time of the fuzzy neural network control system compared with the PID control system is shortened by 24s, the system stability adjustment time is shortened by 160s, and the maximum overshoot is reduced by 6.1%. The research results show that the fuzzy neural network control system can not only realize the adjustment of lithium battery sintering temperature control faster, but also has strong adaptability, fault tolerance and anti-interference ability.
Źródło:
Archives of Foundry Engineering; 2021, 21, 1; 23-30
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust neural networks control of omni-mecanum wheeled robot with Hamilton-Jacobi inequality
Autorzy:
Hendzel, Z.
Powiązania:
https://bibliotekanauki.pl/articles/280641.pdf
Data publikacji:
2018
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
mechatronics
mobile robot
mecanum wheels
Hamilton-Jacobi inequality
Opis:
This paper presents a novel approach to the problem of controlling mechanical objects of unspecified description, considering variable operating conditions. The controlled object is a mobile robot with mecanum wheels (MRK M). To solve the control task, taking into account compensation for nonlinearity and the object variable operating conditions, the Lyapunov stability theory is applied, including the Hamilton-Jacobi (HJ) inequality. A neural network with basic sigmoid functions is used to compensate for the nonlinearity and variable operating conditions of the robot. A simulation example is provided in order to evaluate the analytical considerations. The simulation results obtained confirmed high accuracy of the predicted robot motion in variable operating conditions.
Źródło:
Journal of Theoretical and Applied Mechanics; 2018, 56, 4; 1193-1204
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Wyświetlanie 1-15 z 164

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