DocumentCode :
2437193
Title :
Design of robust optimal controller using neural network
Author :
Kim, Min-Chan ; Park, Seung-Kyu ; Kwak, Gun-Pyong
Author_Institution :
Changwon Nat. Univ., Changwon
fYear :
2007
fDate :
17-20 Oct. 2007
Firstpage :
532
Lastpage :
535
Abstract :
In this paper, a sliding mode controller with neural network sliding surface is proposed. This sliding surface uses the estimation of the relationship between the nominal states by using neural network. In the conventional sliding mode control, the dynamic of sliding surface is not as same as nominal dynamic of original system. To overcome this problem, some research papers with additional dynamic states have been proposed. However this makes the order of a controller become higher. This paper proposes a new design method of a sliding surface without defining any additional dynamic state by using neural network. With this new sliding surface, a robust optimal controller is designed.
Keywords :
control system synthesis; neurocontrollers; optimal control; robust control; variable structure systems; neural network sliding surface; robust optimal control; sliding mode control; Automatic control; Control systems; Design automation; Electronic mail; Neural networks; Optimal control; Robust control; Sliding mode control; State estimation; Uncertain systems; Neural Network; Optimal Control; Sliding mode Control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems, 2007. ICCAS '07. International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-89-950038-6-2
Electronic_ISBN :
978-89-950038-6-2
Type :
conf
DOI :
10.1109/ICCAS.2007.4406967
Filename :
4406967
Link To Document :
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