An Improved Adaptive Neural Network Method for Control System

2006 ◽  
Author(s):  
Lian-ming Wang ◽  
Mu-jun Xie ◽  
Dan-yang Wu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Adaptive Neural Network ◽  
Neural Network Method ◽  
Network Method

Vibration Control System of Precision Dicing Saw Machine Based on Neural Network Method

2014 ◽  
Vol 577 ◽  
pp. 228-231
Author(s):  
Yan Ma ◽  
Xue Feng Bai
Keyword(s):  
Neural Network ◽  
Control System ◽  
Vibration Control ◽  
Neural Network Method ◽  
Compensation Methods ◽  
Network Method ◽  
Feedback Method ◽  
Run Time

The precision dicing machine is adopted as the research object in the paper, the technology of grating sensor is selected to overcome the shortcoming of traditional compensation methods for inaccurate return compensate. The measurement is done through the grating sensor, with the aid of neural network feedback method, the fitting and compensation of the data measured by the grating sensor is completed, the deviation caused by vibration during the spindle run-time is eliminated. And the purpose of improving the precision of spindle is realized.

scholarly journals Neural network method of adaptive control system of imitation of physical forces

2020 ◽  
Vol 28 (3) ◽  
pp. 61-74
Author(s):  
Artem D. Obukhov ◽  
Alexandr A. Siukhin
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Control System ◽  
Control Method ◽  
System Delay ◽  
Neural Network Method ◽  
Machine System ◽  
The Neural Network ◽  
Network Method ◽  
Physical Forces

This research examines the subject area of ​​physical forces simulation systems, implemented on the basis of controlled running platforms. The time spent by the control system to receive and process information about the state of the user and the system causes a software and hardware delay that prevents the system from responding in a timely manner to the user's natural movement. The control system delay problem cannot be solved using direct data of the states of the man-machine system. The aim of the presented research is to develop a new control method that allows analyzing the state of the user and the platform, forecasting his movements and organizing the process of managing the system for simulating physical forces. The method is implemented using neural networks. The scientific novelty of the method includes in the use of neural networks to solve the problems of forecasting user actions and automating decision-making to control the system for simulating physical forces. Each presented neural network is formed to perform separate tasks. The first is to create a forecast of changes in the states of a man-machine system. The second is to determine whether the forecasted state belongs to any state in the historical data. The third determines the required change in the states of the parameters of the man-machine system to achieve the forecasted state. The possibilities of using the described approach are presented on the example of a treadmill that adapts to the real parameters of the user's locomotion. The results obtained confirm a significant reduction in the complexity of the implementation of the control process after applying the neural network method. The area of application of the neural network control method is adaptive information systems and automatic control systems, in which it is necessary to minimize the system delay time and response to user locomotion.

scholarly journals Control of a Ball on Sphere System with Adaptive Neural Network Method for Regulation Purpose

2014 ◽  
Vol 14 (17) ◽  
pp. 1984-1989 ◽  
Author(s):  
Seyed Alireza Mo ◽  
Ehsan Zakeri ◽  
Yousef Bazargan-L ◽  
Mohammad Tavallaein
Keyword(s):  
Neural Network ◽  
Adaptive Neural Network ◽  
Neural Network Method ◽  
Network Method

Methods for evaluation the manufacturability of a vehicle

2020 ◽  
pp. 152-160
Keyword(s):  
Neural Network ◽  
Initial Data ◽  
Comparative Data ◽  
Training Algorithm ◽  
Neural Network Method ◽  
The Neural Network ◽  
Network Method ◽  
Calculation Results ◽  
Production And Operation

Methods for evaluation the manufacturability of a vehicle in the field of production and operation based on an energy indicator, expert estimates and usage of a neural network are stated. By using the neural network method the manufacturability of a car in a complex and for individual units is considered. The preparation of the initial data at usage a neural network for predicting the manufacturability of a vehicle is shown; the training algorithm and the architecture for calculating the manufacturability of the main units are given. According to the calculation results, comparative data on the manufacturability vehicles of various brands are given.

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