Application of Fuzzy Predictive Control in Superheated Steam Temperature Control

2006 ◽  
Author(s):  
Na Wang ◽  
Song-ming Jiao ◽  
Dong-feng Wang ◽  
Shou-rong Qi ◽  
Pu Han
Keyword(s):  
Predictive Control ◽  
Temperature Control ◽  
Superheated Steam ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Fuzzy Predictive Control

Superheated Steam Temperature Control Based on Improved Recurrent Neural Network and Simplified PSO Algorithm

2011 ◽  
Vol 128-129 ◽  
pp. 1065-1069 ◽  
Author(s):  
Liang Yu Ma ◽  
Yin Ping Ge ◽  
Xing Cao
Keyword(s):  
Neural Network ◽  
Temperature Control ◽  
Recurrent Neural Network ◽  
Power Plants ◽  
Superheated Steam ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Control Scheme ◽  
Wide Range ◽  
Optimization Control

Coal-fired power plants are facing a rapid developing tide toward supercritical and ultra-supercritical boiler units with higher parameters and bigger capacity. Due to the large inertia, large time delay and nonlinear characteristics of a boiler’s superheater system, the widely-used conventional cascade PID control scheme is often difficult to obtain satisfactory steam temperature control effect under wide-range operating condition. In this paper, a predictive optimization control method based on improved mixed-structure recurrent neural network model and a simpler Particle Swarm Optimization (sPSO) algorithm is presented for superheated steam temperature control. Control simulation tests on the full-scope simulator of a 600 MW supercritical power unit showed that the proposed predictive optimization control scheme can greatly improve the superheated steam temperature control quality with good application prospect.

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