DocumentCode :
2246379
Title :
Research on PID control based on BP neural network and its application
Author :
Shuangxi, Gao ; Shufu, Cao ; Ying, Zhang
Author_Institution :
Coll. of Inf. & Technol., Hebei Univ. of Econ. & Bus., Shijiazhuang, China
Volume :
2
fYear :
2010
fDate :
6-7 March 2010
Firstpage :
91
Lastpage :
94
Abstract :
BP (Back-propagation) neural network and conventional PID (Piping and Instrument Diagram) control combined. A PID control strategy of self-adjusting parameter brought forward. It solved the problems of the parameter certain complex and large computational quantity and realizes online adjustment PID parameters. According to control characteristic of PH value adjustment links in sewage treatment system, BP network training arithmetic and the corresponding control arithmetic designed. Experimental results show that the sewage treatment system of PID control based on BP neural network has these characteristics such as fast response, high steady-state accuracy and strong robustness and so on.
Keywords :
backpropagation; neurocontrollers; nonlinear control systems; pH control; sewage treatment; three-term control; time-varying systems; BP network training arithmetic; BP neural network; PH value adjustment; PID control research; backpropagation; control arithmetic; piping and instrument diagram control; self adjusting parameter; sewage treatment system; steady state accuracy; Automatic control; Communication system control; Control systems; Error correction; Neural networks; Pi control; Proportional control; Sewage treatment; Steady-state; Three-term control; BP neural network; PH value adjustment; PID;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
ISSN :
1948-3414
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
Type :
conf
DOI :
10.1109/CAR.2010.5456629
Filename :
5456629
Link To Document :
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