DocumentCode :
3573513
Title :
Data-driven-based superheated steam temperature control of fossil fuel power generation units
Author :
Huifang Guo ; Fang Fang ; Le Wei
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
fYear :
2014
Firstpage :
4809
Lastpage :
4814
Abstract :
In modern industry, data has become an indispensible resource for the whole process of production and business. For the optimization of the control performance, the data-driven PID controller is introduced in this paper. Based on the data-driven control law, the parameters of the PID controller will be renewed automatically by using the real and historical input/output data of the plant. And then, the control action can be update in real time. From the perspective of engineering applications, the data-driven PID controller is researched as the outer loop controller in the superheated steam temperature cascade control system of fossil fuel power generation units. The simulation results show that the data-driven PID controller is suitable for the superheated steam temperature control, and its performance is better than that of the neural network PID controller.
Keywords :
cascade control; fossil fuels; neural nets; power generation control; steam power stations; temperature control; three-term control; cascade control system; data-driven PID controller; data-driven control law; fossil fuel power generation unit; neural network; outer loop controller; superheated steam temperature control; Databases; Neural networks; PD control; Temperature; Temperature control; Vectors; Data-driven; PID control; superheated steam temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7053527
Filename :
7053527
Link To Document :
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