Single neuron self-adaptive PSD control and its application in reheat steam temperature control system

2002 ◽  
Author(s):  
Zhao Xiling ◽  
Jiao Yunting
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Single Neuron ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Reheat Steam ◽  
Self Adaptive

scholarly journals Performance Analysis of Reheat Steam Temperature Control System of Thermal Power Unit Based on Constrained Predictive Control

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoli Li ◽  
Jian Liu ◽  
Kang Wang ◽  
Fuqiang Wang ◽  
Yang Li
Keyword(s):  
Control System ◽  
Steady State ◽  
Power Unit ◽  
Predictive Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Thermal Power ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Reheat Steam

The reheat steam temperature control system of thermal power unit is a complex control object with time-varying parameters and large delay. In order to achieve precise control of reheat steam temperature, the performance of the reheat temperature control system is analyzed according to the data that are obtained based on the constrained predictive control algorithm. Firstly, the process and mathematical model of reheat steam temperature control system are introduced. Then the principle of constrained predictive control algorithm is analyzed. Finally, the steady-state values of control quantities of reheat steam temperature control system under different conditions are given by MATLAB simulation, and, by analyzing the steady-state values and steady-state time of the input and output of the system, the reference values and the regulating law of the control quantities and the specific constraint range of the control quantities of the system are given, which can provide reference data and theoretical basis for the field adjustment of the reheat steam temperature control system in power plant and improve the safety and effectiveness of the system.

Study on Applications of State Feedback Based on NN Observer in Super-Heated Steam Temperature Control

2005 ◽  
Author(s):  
Luanying Zhang ◽  
Zhiming Qin ◽  
Junjie Gu
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Pid Control ◽  
State Feedback ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Elman Neural Network ◽  
Network State ◽  
Cascade Control System ◽  
Better Than

It is difficult for the conventional PID control to adjust with the change of dynamic characteristics of the plants. By combing the state feedback based on Elman neural network state observer and the conventional PID, a new control system was presented in this paper. The unmeasurable states of the system was reconstructed through NN observer, the adaptivabilty of system was improved by state feedback. A simulation for power plant super-heated steam temperature control system using presented method is carried out, and resulting in that the control system performance is better than the conventional cascade control system.

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