DocumentCode
2483276
Title
Identification research on improved PID neural network and its application
Author
Shen, Yongjun ; Gu, Xingsheng ; Bao, Qiong
Author_Institution
Res. Inst. of Autom., East China Univ. of Sci. & Technol., Shanghai
fYear
2008
fDate
25-27 June 2008
Firstpage
2542
Lastpage
2547
Abstract
PID neural network (PID-NN) is a new type of dynamic feed-forward network which combines neural network with PID control strategy. It performs a perfect function in process control with the merit of both general PID controller and neural network. In this paper, the concepts of variable integral and partial differential are introduced in the design of hidden-layer of PID-NN to improve the capabilities of neurons. The structure of system identification is analyzed, and the results of simulation with field data of wet FGD indicate the validity and superiority of this improved modeling approach.
Keywords
feedforward; neurocontrollers; partial differential equations; three-term control; PID control strategy; PID neural network; dynamic feed-forward network; partial differential; variable integral; Automatic control; Automation; Electronic mail; Feedforward neural networks; Feedforward systems; Intelligent control; Neural networks; Neurons; Process control; Three-term control; ID neural network; identification; partial differential; variable integral;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4593323
Filename
4593323
Link To Document