Generalized Predictive Control Algorithm Applied to Thermal Power Units Based on Fuzzy Neural Network

2011 ◽  
Author(s):  
Wei Sun ◽  
Hujun Ling
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Control Algorithm ◽  
Fuzzy Neural Network ◽  
Thermal Power ◽  
Generalized Predictive Control ◽  
Fuzzy Neural

The Application of Fuzzy Neural Network Generalized Predictive Control in Unit Plant Coordinated Control System

2014 ◽  
Vol 602-605 ◽  
pp. 1329-1331
Author(s):  
Shu Zhang ◽  
Hu Jun Ling ◽  
Zhen Lin Zhang ◽  
Meng Jie Hu ◽  
Yang Pang
Keyword(s):  
Neural Network ◽  
Mathematical Models ◽  
Predictive Control ◽  
Power Plants ◽  
Fuzzy Neural Network ◽  
Thermal Power ◽  
Coordinated Control ◽  
Steam Pressure ◽  
Generalized Predictive Control ◽  
Fuzzy Neural

The characteristic of unit coordinated control in thermal power plants having complex, nonlinear, larger time delay, and establishing mathematical models are very difficult. In the paper establish mathematical models of using fuzzy neural network system, make full use of the ability of fuzzy logic reasoning and neural network self-learning; using multivariable generalized predictive control strategy, Simulation results show that the use of fuzzy neural network generalized predictive control for good stability of main steam pressure , strong effectiveness of tracking the power grid load, and little fluctuation of different load conversion.

scholarly journals Synchronization Control Algorithm of Double-Cylinder Forging Hydraulic Press Based on Fuzzy Neural Network

Algorithms ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 63
Author(s):  
Xiaodan Xu ◽  
Zhifeng Bai ◽  
Yuanyuan Shao
Keyword(s):  
Neural Network ◽  
Transfer Function ◽  
Balance Equation ◽  
Control Algorithm ◽  
Fuzzy Neural Network ◽  
Hydraulic Cylinder ◽  
Hydraulic Press ◽  
Amplitude Curve ◽  
Synchronous Control ◽  
Fuzzy Neural

In order to solve the poor control accuracy problem of the traditional synchronous control algorithm for a double-cylinder forging hydraulic press, a synchronous control algorithm for double-cylinder forging hydraulic press based on a fuzzy neural network was proposed. According to the flow equation of valve and hydraulic cylinder, the balance equation and force balance equation of forging hydraulic cylinder are established by using the theory of electro-hydraulic servo systems, and the cylinder-controlled transfer function of forging hydraulic cylinder is deduced. By properly simplifying the transfer function, the mathematical model of synchronous control of double cylinder forging hydraulic press is established. According to the implementation process of traditional fuzzy neural networks, the properties of compensation operation are introduced. The traditional fuzzy neural network is optimized, and the optimized neural network is used to realize the synchronous control of the double cylinder forging hydraulic press. The experimental results show that the amplitude curve of the algorithm is very close to the expected amplitude curve, the error amplitude is only 0.3 mm, and the average control time is about 140 s, which fully shows that the algorithm has high accuracy and a good control effect.

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