Adaptive Neuro-control System for Superheated Steam Temperature of Power Plant over Wide Range Operation

2006 ◽  
Author(s):  
Jianhua Zhang ◽  
Guolian Hou ◽  
Jinfang Zhang
Keyword(s):  
Control System ◽  
Power Plant ◽  
Superheated Steam ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Wide Range

Adaptive PID Cascade Control for Superheated Steam Temperature Based on Inverse Model

2011 ◽  
Vol 133 (11) ◽  
Author(s):  
Zhijie Wang ◽  
Guangjun Wang ◽  
Hong Chen
Keyword(s):  
Control System ◽  
Power Plant ◽  
Superheated Steam ◽  
Thermal Power ◽  
Control Process ◽  
Inverse Model ◽  
Cascade Control ◽  
Steam Temperature ◽  
Superheated Steam Temperature ◽  
Cascade Control System

Since the superheated steam temperature system of boiler in thermal power plant is characterized as time varying and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportional-integral-derivative (PID) cascade control scheme. This paper presents a design method of adaptive PID cascade control system for superheated steam temperature based on inverse model: First, the inner loop and the outer process in the cascade control system are equivalent to a generalized plant. A simplified Takagi–Sugeno (STS) fuzzy model is adopted to identify the inverse model of the generalized plant. By choosing the appropriate structure and optimizing with constrains for the parameters of the inverse model, the organic combination of the PID primary controller with the inverse model is realized. To maintain the structure of the existing conventional PID cascade control system in power plant without change, in the control process, the parameters of the primary controller are adjusted on-line according to the identification result of the inverse model of the generalized plant; thus an adaptive PID cascade control system is formed, which matches with the characteristics of the controlled plant. Through the simulation experiments of controlling superheated steam temperature, it is illustrated that the proposed scheme has good adaptability and anti-interference ability.

scholarly journals Generalized Predictive Control for superheated steam temperature regulation in a supercritical coal-fired power plant

2015 ◽  
Vol 1 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Mihai Draganescu ◽  
Shen Guo ◽  
Jacek Wojcik ◽  
Jihong Wang ◽  
Xiangjie Liu ◽  
...  
Keyword(s):  
Power Plant ◽  
Predictive Control ◽  
Temperature Regulation ◽  
Superheated Steam ◽  
Generalized Predictive Control ◽  
Steam Temperature ◽  
Superheated Steam Temperature

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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