Research of Constant Pressure Delivery PID Control System of Flying Ashes

Authors

Yanjun Xiao, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;
Yingpei Sun, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;
Xianle Meng, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;
Yongcong Li, School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;

Abstract

Abstract: Comparing to the drawbacks of fly ash constant current conveying system, the advantages of constant pressure delivery system and its conveying theory were introduced. A scientific modeling of the key of PID controller was established. By introducing the fuzzy control algorithm, the fly ash constant pressure conveying fuzzy adaptive PID controller was designed, which could make the auto changes between the fuzzy control and PID controller come true, and the simulation with MATLAB was researched. The results show that fuzzy adaptive PID controller is superior to the conventional PID controller in overshoot, response speed and adjusting time. And fuzzy adaptive PID controller has advantages of static and dynamic performance, intellectuality and robustness. It provides a powerfully theoretical guidance and basis for engineering practice of the followed flying-ashes-system. It is positively significant to further enhance the level of automation.

Recommended Citation

Xiao, Yanjun; Sun, Yingpei; Meng, Xianle; and Li, Yongcong (2020) "Research of Constant Pressure Delivery PID Control System of Flying Ashes," Journal of System Simulation: Vol. 27: Iss. 1, Article 23.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss1/23

First Page

171

Revised Date

2014-06-18

DOI Link

https://doi.org/

Last Page

178

CLC

TP391.9

Recommended Citation

Xiao Yanjun, Sun Yingpei, Meng Xianle, Li Yongcong. Research of Constant Pressure Delivery PID Control System of Flying Ashes[J]. Journal of System Simulation, 2015, 27(1): 171-178.