An Ensemble of Neural Networks for Control System Application

2012 ◽  
Author(s):  
Alvin Sahroni
Keyword(s):  
Neural Networks ◽  
Control System ◽  
System Application

Modeling of Self-Induced Vibrations that Occur During the Machining Process of Casting Patterns with the Use of The Fuzzy-Neural Networks Method

2013 ◽  
Vol 58 (3) ◽  
pp. 871-875
Author(s):  
A. Herberg
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Network Structure ◽  
Fuzzy Systems ◽  
Fuzzy Neural Networks ◽  
Cnc Machining ◽  
Machining Process ◽  
Modeling Process ◽  
Fuzzy Neural ◽  
Takagi Sugeno

Abstract This article outlines a methodology of modeling self-induced vibrations that occur in the course of machining of metal objects, i.e. when shaping casting patterns on CNC machining centers. The modeling process presented here is based on an algorithm that makes use of local model fuzzy-neural networks. The algorithm falls back on the advantages of fuzzy systems with Takagi-Sugeno-Kanga (TSK) consequences and neural networks with auxiliary modules that help optimize and shorten the time needed to identify the best possible network structure. The modeling of self-induced vibrations allows analyzing how the vibrations come into being. This in turn makes it possible to develop effective ways of eliminating these vibrations and, ultimately, designing a practical control system that would dispose of the vibrations altogether.

Combination of Neural Networks and State Vector Feedback Adaptive Control (SVFAC) Technique to Control the Gas Turbine Combustor

2006 ◽  
Author(s):  
Mahmood Lahroodi ◽  
A. A. Mozafari
Keyword(s):  
Neural Networks ◽  
Adaptive Control ◽  
Control System ◽  
Gas Turbine ◽  
Control Method ◽  
Control Performance ◽  
Gas Turbine Combustor ◽  
Model Network ◽  
Neural Network Controller ◽  
Nonlinear Plants

Neural networks have been applied very successfully in the identification and control of dynamic systems. When designing a control system to ensure the safe and automatic operation of the gas turbine combustor, it is necessary to be able to predict temperature and pressure levels and outlet flow rate throughout the gas turbine combustor to use them for selection of control parameters. This paper describes a nonlinear SVFAC controller scheme for gas turbine combustor. In order to achieve the satisfied control performance, we have to consider the affection of nonlinear factors contained in controller. The neural network controller learns to produce the input selected by the optimization process. The controller is adaptively trained to force the plant output to track a reference output. Proposed Adaptive control system configuration uses two neural networks: a controller network and a model network. The model network is used to predict the effect of controller changes on plant output, which allows the updating of controller parameters. This paper presents the new adaptive SFVC controller using neural networks with compensation for nonlinear plants. The control performance of designed controller is compared with inverse control method and results have shown that the proposed method has good performance for nonlinear plants such as gas turbine combustor.

Globalized Dual Heuristic Dynamic Programming in Control of Robotic Manipulator

2016 ◽  
Vol 817 ◽  
pp. 150-161 ◽  
Author(s):  
Marcin Szuster ◽  
Piotr Gierlak
Keyword(s):  
Neural Networks ◽  
Dynamic Programming ◽  
Control System ◽  
Degrees Of Freedom ◽  
Dynamic Programming Algorithm ◽  
Robotic Manipulator ◽  
Iteration Step ◽  
Programming Algorithm ◽  
Heuristic Dynamic Programming ◽  
The Stability

The article focuses on the implementation of the globalized dual-heuristic dynamic programming algorithm in the discrete tracking control system of the three degrees of freedom robotic manipulator. The globalized dual-heuristic dynamic programming algorithm is included in the approximate dynamic programming algorithms family, that bases on the Bellman’s dynamic programming idea. These algorithms generally consist of the actor and the critic structures realized in a form of artificial neural networks. Moreover, the control system includes the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis, which was realized using the Lyapunov stability theorem. The control system works on-line and the neural networks’ weight adaptation process is realized in every iteration step. A series of computer simulations was realized in Matlab/Simulink software to confirm performance of the control system.

scholarly journals Rancang Bangun Sistem Kontrol Keamanan Gerbang Menggunakan Raspberry Pi B+ Berbasis Web

2021 ◽  
Vol 7 (1) ◽  
pp. 10-18
Author(s):  
Arief Saptono ◽  
Abdul Malik ◽  
Muhamad Satim
Keyword(s):  
Control System ◽  
System Application ◽  
Control Process ◽  
Control Device ◽  
Security System ◽  
Raspberry Pi ◽  
Web Browser ◽  
Security Control ◽  
Web Camera ◽  
Gate Control

Computer and information technology from time to time are always experiencing developments, both in terms of hardware, software and the internet being one of the most important things atthis time. The increasing number of applications of computer technology will make the role of computers increasingly important to be more advanced (modernization). The security system isstill not effective and efficient enough, so that a control using a website is needed to help the security control process at the gate. This system is not only used in offices, but can be used inhome security, etc. So we need a security system, where the security control system uses a tool to monitor realtime security via a web browser, namely a webcam (Web Camera). A web-basedgate control system can be designed using the Raspberry Pi B +. From the explanation mentioned above, the researcher made a gate control device that was given to the Microcontroller using a Web Browser in order to open and close the gate. So it is hoped that this security system application can provide a sense of comfort, in addition, of course, with this system application it can reduce the number of crimes that occur both crimes and other crimes.

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