Self-learning neural network fuzzy control applied to the synthetic ammonia production

2002 ◽  
Author(s):  
Shaoyuan Li ◽  
Yugeng Xi ◽  
Wang Xiaoye
Keyword(s):  
Neural Network ◽  
Fuzzy Control ◽  
Ammonia Production ◽  
Self Learning

Adaptive Neural Network Fuzzy Control Plane Double Inverted Pendulum

2013 ◽  
Vol 765-767 ◽  
pp. 2004-2007
Author(s):  
Su Ying Zhang ◽  
Ying Wang ◽  
Jie Liu ◽  
Xiao Xue Zhao
Keyword(s):  
Neural Network ◽  
Fuzzy Control ◽  
Control Theory ◽  
Inverted Pendulum ◽  
Learning Ability ◽  
Adaptive Neural Network ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Self Learning ◽  
Controlled Object

Double inverted pendulum system is nonlinear and unstable. Fuzzy control uses some expert's experience knowledge and learns approximate reasoning algorithm. For it does not depend on the mathematical model of controlled object, it has been widely used for years. In practical engineering applications, most systems are nonlinear time-varying parameter systems. As the fuzzy control theory lacks of on-line self-learning and adaptive ability, it can not control the controlled object effectively. In order to compensate for these defects, it introduced adaptive, self-organizing, self-learning functions of neural network algorithm. We called it adaptive neural network fuzzy inference system (ANFIS). ANFIS not only takes advantage of the fuzzy control theory of abstract ability, the nonlinear processing ability, but also makes use of the autonomous learning ability of neural network, the arbitrary function approximation ability. The controller was applied to double inverted pendulum system and the simulation results showed that this method can effectively control the double inverted pendulum system.

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.

Fuzzy control using neural network techniques

1990 ◽  
Author(s):  
T. Iwata ◽  
K. Machida ◽  
Y. Toda
Keyword(s):  
Neural Network ◽  
Fuzzy Control

Study for Workpiece Identity Based on the BP Neural Network and the Zernike Moment

2013 ◽  
Vol 694-697 ◽  
pp. 1958-1963 ◽  
Author(s):  
Xian Wei ◽  
Jing Dong Zhang ◽  
Xue Mei Qi
Keyword(s):  
Neural Network ◽  
Fault Tolerance ◽  
Parallel Processing ◽  
Bp Neural Network ◽  
Complex Shape ◽  
Learning Ability ◽  
Zernike Moment ◽  
Recognition Ability ◽  
Identity Based ◽  
Self Learning

The robots identify, locate and install the workpiece in FMS system by identifying the characteristic information of target workpiece. The paper studied the recognition technology of complex shape workpiece with combination of BP neural network and Zernike moment. The strong recognition ability of Zernike moment can extract the characteristic. The good fault tolerance, classification, parallel processing and self-learning ability of BP neural network can greatly improve the accurate rate of recognition. Experimental results show the effectiveness of the proposed method.

THE CONCEPT OF MANAGING THE DATA NETWORK BASED ON SELF-LEARNING SYSTEMS

2020 ◽  
Author(s):  
С.Р. РОМАНОВ
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Transmission ◽  
Network Control ◽  
Learning Systems ◽  
Optimal Routing ◽  
Transmission Network ◽  
Data Traffic ◽  
Data Network ◽  
Self Learning

Рассмотрен принцип управления сетью передачи данных (СПД)с помощью искусственной нейронной сети. Предложена концепция проведения вычислений при решении задачи оптимальной маршрутизации трафика данных. Приведен алгоритм управления сетью СПД на базе нейронной сети Хэмминга. The principle of data transmission network control using an artificial neural network is considered. The concept of carrying out calculations when solving the problem of optimal routing of data traffic is proposed. The algorithm for controlling the data transmission network based on the Hamming neural network is presented.

The Application of Neural Network in Computer Control

2013 ◽  
Vol 380-384 ◽  
pp. 421-424
Author(s):  
Jing Liu ◽  
Yu Chi Zhao ◽  
Xiao Hua Shi ◽  
Su Juan Liu
Keyword(s):  
Neural Network ◽  
Distributed Storage ◽  
Computer Control ◽  
System Optimization ◽  
Good Choice ◽  
Information Storage ◽  
Knowledge Process ◽  
Control Computer ◽  
Self Learning ◽  
Logic System

In recent years, it is a very active direction of research to use neural network to control computer. Neural network is a burgeoning crossing subject, and the way it processes information is different from the past symbolic logic system, which has some unique properties: such as the distributed storage and parallel processing of information, the unity of the information storage and information processing, and have the ability of self-organizing and self-learning. And it has been applied widespread in pattern recognition, signal processing, knowledge process, expert system, optimization, intelligent control and so on. Using neural network can deal with some problems such as complicated environment information, fuzzy background knowledge and undefined inference rules, and it allows samples to have relatively large defects and distortion, so it is a very good choice to adopt the recognizing method of neural network. This thesis discusses the application of neural network in computer control.

Sign in / Sign up

Export Citation Format

Share Document