Online learning neural network controller for pneumatic robot position control

2002 ◽  
Author(s):  
Wang Qi ◽  
Tao Qian ◽  
Hou Linqi ◽  
Cai Hegao
Keyword(s):  
Neural Network ◽  
Online Learning ◽  
Position Control ◽  
Neural Network Controller ◽  
Network Controller ◽  
Robot Position

Position control of an er valve-cylinder system via neural network controller

Mechatronics ◽  
1997 ◽  
Vol 7 (1) ◽  
pp. 37-52 ◽  
Author(s):  
S.B. Choi ◽  
C.C. Cheong ◽  
J.M. Jung ◽  
Y.T. Choi
Keyword(s):  
Neural Network ◽  
Position Control ◽  
Neural Network Controller ◽  
Network Controller

scholarly journals Adaptive Inverse Neural Network Based DC Motor Speed and Position Control Using FPGA

2018 ◽  
Vol 11 (3) ◽  
pp. 71-78
Author(s):  
Aula N. Abd
Keyword(s):  
Neural Network ◽  
Pid Controller ◽  
Position Control ◽  
Back Propagation ◽  
Dc Motor ◽  
Motor Speed ◽  
Back Propagation Algorithm ◽  
Neural Network Controller ◽  
Network Controller ◽  
Field Programmable

In this research two types of controllers are designed in order to control the speed and position of DC motor. The first one is a conventional PID controller and the other is an intelligent Neural Network (NN) controller that generate a control signal DC motor. Due to nonlinear parameters and movable laborers such saturation and change in load a conventional PID controller is not efficient in such application; therefore neural controller is proposed in order to decreasing the effect of these parameter and improve system performance. The proposed intelligent NN controller is adaptive inverse neural network controller designed and implemented on Field Programmable Gate Array (FPGA) board. This NN is trained by Levenberg-Marquardt back propagation algorithm. After implementation on FPGA, the response appear completely the same as simulation response before implementation that mean the controller based on FPGA is very nigh to software designed controller. The controllers designed by both m-file and Simulink in MATLAB R2012a version 7.14.0.

Online Learning Artificial Neural Network Controller for a Buck Converter

2019 ◽  
Author(s):  
Jazmin Ramirez-Hernandez ◽  
Oswaldo Ulises Juarez-Sandoval ◽  
Kevin Cano-Pulido ◽  
Juan Francisco Marquez-Rubio ◽  
Nancy Mondragon-Escamilla
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Online Learning ◽  
Buck Converter ◽  
Neural Network Controller ◽  
Network Controller ◽  
Artificial Neural

Research on Intelligent Variable Frequency of Air-Conditioner Control System Based on Fuzzy Control

2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Neural Network ◽  
Air Conditioner ◽  
Neural Network Controller ◽  
The Neural Network ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Fuzzy Control Strategy

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.

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