Title :
The study and simulation of PID control based on RBF neural network
Author :
Chen Yi-fei ; Xu Sen ; Cao Rui ; Zhou Tian
Author_Institution :
Sch. of Inf. Eng., Yancheng Inst. of Technol., Yancheng, China
Abstract :
The industrial control system is a complex nonlinear time-varying system, the traditional PID control is limited to linear system, and therefore the control effect is not ideal. In order to improve the control precision, this paper proposes a control method based on RBF neural network and. Firstly discrete models is identification by RBFNN controller and get PID parameters tuning information, then use single neuron controller to set the parameter so as to realize the intelligent control system. The proposed method is verified, the results show that the control method has faster response time, higher control precision compared with the traditional PID control methods; it is a strong adaptability, robustness and anti-interference ability.
Keywords :
discrete systems; industrial control; neurocontrollers; nonlinear control systems; radial basis function networks; three-term control; time-varying systems; PID control methods; RBF neural network; antiinterference ability; control precision; discrete models; industrial control system; intelligent control system; nonlinear time-varying system; parameters tuning information; single neuron controller; Biological neural networks; Control systems; Genetic algorithms; Neurons; Object recognition; Optimization; Radial basis function networks; PID control; RBF neural network; identification; nonlinear systems;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6023826
