Title :
Adaptive Prediction PID Control Based on RBFNN
Author :
Minghe, Li ; Meng, Wang ; Yanyan, Shi
Author_Institution :
Anhui Univ. of Technol., Maanshan
Abstract :
To system which is of long time-delay in the industrial control fields, a control method of adaptive predictive PID control based on RBF neural network (RBFNN) is presented. The dynamic behavior of control object in the future time is implemented more accurately by the description of Predictive model based on RBFNN trained by clustering and the self-tuning of controller parameters was implemented by the RBFNN controller. The simulation result indicates that the system possesses the advantages of high precision, quick response speed and is of great adaptability and robustness.
Keywords :
intelligent control; radial basis function networks; three-term control; PID control; RBF neural network; adaptive prediction; clustering; control object; dynamic behavior; long time-delay; self-tuning; Adaptive control; Clustering algorithms; Control systems; Instruments; Neural networks; Optimal control; Predictive models; Programmable control; Robustness; Three-term control; Clustering; Prediction; RBFNN; Time-delay;
Conference_Titel :
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-1136-8
Electronic_ISBN :
978-1-4244-1136-8
DOI :
10.1109/ICEMI.2007.4350994
