A dynamic weight-fuzzy neural network for nonlinear dynamic system control

2005 ◽  
Author(s):  
D.P. Kwok ◽  
C.K. Li ◽  
T.P. Leung ◽  
Z.D. Deng ◽  
Z.Q. Sun
Keyword(s):  
Neural Network ◽  
Dynamic System ◽  
Nonlinear Dynamic ◽  
Fuzzy Neural Network ◽  
Nonlinear Dynamic System ◽  
System Control ◽  
Dynamic Weight ◽  
Fuzzy Neural

Identification of Multivariable Nonlinear Dynamic System Based on PID Neural Network

2015 ◽  
Vol 719-720 ◽  
pp. 475-481
Author(s):  
Hua Shu ◽  
Huai Lin Shu
Keyword(s):  
Neural Network ◽  
System Identification ◽  
Dynamic System ◽  
Nonlinear Dynamic ◽  
Linear Time ◽  
Nonlinear Dynamic System ◽  
Identification Methods ◽  
Linear Time Invariant ◽  
Linear Time Invariant Systems ◽  
Pid Neural Network

System identification is the basis for control system design. For linear time-invariant systems have a variety of identification methods, identification methods for nonlinear dynamic system is still in the exploratory stage. Nonlinear identification method based on neural network is a simple and effective general method that does not require too much priori experience about the system to be identified. Through training and learning, the network weights are corrected to achieve the purpose of system identification. The paper is about the identification of multivariable nonlinear dynamic system based on PID neural network. The structure and algorithm of PID neural network are introduced and the properties and characteristics are analyzed. The system identification is completed and the results are fast convergence.

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