Application of Two Fractional Differential Equations Based on Competitive Neural Network Algorithm in Control System

2020 ◽  
Vol 29 (3) ◽  
Author(s):  
Feng Baolin ◽  
Feng Xue ◽  
Chuang Yao ◽  
Qiao Xing
Keyword(s):  
Neural Network ◽  
Control System ◽  
Differential Equations ◽  
Fractional Differential Equations ◽  
Competitive Neural Network ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Fractional Differential

Research of BP Neural Network Algorithm Testing Platform Based on OPC Communication

2014 ◽  
Vol 668-669 ◽  
pp. 575-580
Author(s):  
Bing Wu Chen ◽  
Xing Chen ◽  
Hui Peng Shu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Real Time ◽  
Bp Neural Network ◽  
Data Exchange ◽  
Communication Process ◽  
Effective Control ◽  
Testing Platform ◽  
Network Algorithm ◽  
Neural Network Algorithm

Effective control algorithm can be applied to the real-time control system by the data exchange between MCGS and MATLAB with OPC technology, as a result, a testing platform for advanced control algorithms is established. The paper presents a second-order liquid level control system for research example; the BP neural network algorithm is applied to the control system. The communication process verifies that the data exchange is reliable and the simulation results show the control of the BP neural network algorithm for real-time optimized control process is effective.

scholarly journals Fuzzy Neural Network Algorithm in Improving Electrical Engineering Control System

2021 ◽  
Vol 2074 (1) ◽  
pp. 012080
Author(s):  
Xiaotao Tian
Keyword(s):  
Neural Network ◽  
Control System ◽  
Electrical Engineering ◽  
Electrical Control ◽  
Intelligent Control System ◽  
Engineering Control ◽  
Network Algorithm ◽  
Fuzzy Neural ◽  
Artificial Intelligence Technology ◽  
Neural Network Algorithm

Abstract In the current era of rapid development of big data technology and artificial intelligence technology, China’s comprehensive national strength has also been significantly enhanced, the rapid progress of science and technology makes the electrical engineering control system whether in terms of efficiency and quality of the application, its electrical engineering control system development is gradually improved with the support of high-tech. Based on artificial intelligence technology, neural network algorithms and improved neural network algorithms are proposed to improve the original electrical engineering control system. In this paper, the S electrical engineering control system is the main research object, and its addition of fuzzy neural network algorithm to improve the study. Firstly, on the basis of a simple description of S electrical control system, the research status of the main partition control blocks of S electrical control system is analyzed. Secondly, an improved intelligent control system, including intelligent service interruption system and central electrical control system, is proposed to design an improved electrical engineering control system based on neural network algorithm through the operation principle of sensors and the study of network communication technology. Based on the above research basis, the effectiveness and practicality of the proposed intelligent electrical engineering control system are verified by analyzing the effects of the proposed intelligent electrical engineering control system in real life. The experimental results show that although there are still many problems in the intelligent control system of three-phase electrical engineering at this stage, innovation and technological progress will continuously improve the comprehensiveness and intelligence level of the system.

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