DocumentCode
2093683
Title
Nonlinear robust controller tuning based on artificial neural network
Author
Chen Yafeng ; Li Donghai ; Lao Dazhong
Author_Institution
Sch. of Aerosp. Eng., Beijing Inst. of Technol., Beijing, China
fYear
2010
fDate
29-31 July 2010
Firstpage
6056
Lastpage
6060
Abstract
The tuning method of nonlinear robust controller (NRC) for plants based on artificial neural network (ANN) is proposed, employing the nonlinear mapping features of ANN and ITAE, rise time and overshoot as the control performance criteria. The NRC control tuning rules are verified using Monte-Carlo experiments. The relationship between the parameters and stability of the control system is analyzed.
Keywords
Monte Carlo methods; control system analysis; neurocontrollers; nonlinear control systems; robust control; tuning; Monte-Carlo experiment; artificial neural network; nonlinear mapping features; nonlinear robust controller; overshoot; rise time; stability; tuning method; Artificial neural networks; Control systems; Electronic mail; Robustness; Stability analysis; Thermal engineering; Tuning; Artificial Neural Network; Monte-Carlo Experiment; Nonlinear Robust Controller; Parameters Tuning;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2010 29th Chinese
Conference_Location
Beijing
Print_ISBN
978-1-4244-6263-6
Type
conf
Filename
5572907
Link To Document