Title :
Control study of long time delay process based on improved grey predictive model
Author :
Junfeng, Liu ; Aisheng, Xia ; Junjian, Xia ; Baoan, Hu
Author_Institution :
Dept. of Basic Sci., Mil. Transp. Univ., Tianjin, China
Abstract :
To the problem of the traditional PID method is hard to achieve satisfied result in long time delay process, GM(2,1) grey model is predict used to the behavior of controlled process, and the model is improved by using “moving window” and changing the initiate condition. The coefficient of the GM(2,1) model is applied to determine the prediction steps. By combining GM(2,1) model with PID, the grey predicting control system for controlling the long time delay process is proposed. The results of simulation show that, comparing with traditional PID control method, the proposed algorithm has better flexibility and robustness, and also can fairly improve the control performances.
Keywords :
delays; grey systems; predictive control; three-term control; PID method; control study; grey predictive model improvement; long time delay process; Control systems; Data models; Delay; Delay effects; Mathematical model; Predictive models; Process control; GM(2,1) model; Grey prediction; Long time delay process; Predictive control;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244130