DocumentCode :
3717877
Title :
A multi-dimensional Taylor network (MTN)-based approach for nonlinear stochastic systems tracking control
Author :
Yu-Qun Han;Hong-Sen Yan
Author_Institution :
School of Automation, Southeast University, Nanjing, 210096, China
fYear :
2015
Firstpage :
892
Lastpage :
896
Abstract :
The problem of tracking control for stochastic nonlinear systems is investigated in this paper. Because of the randomness and nonlinearity of stochastic nonlinear systems, the existing methods are sometimes difficult to achieve the desired tracking performance. In this paper, a new network controller (multi-dimensional Taylor network) is proposed, which only relies on the output of system. Firstly we give the structure of multi-dimensional Taylor network (MTN), and then prove the MTN has a good approximation performance. Secondly, Design a MTN control strategy relying on the system output, which will guarantee the tracking of system output to desired output. An example is given to illustrate the effectiveness of the proposed design approach.
Keywords :
"Artificial neural networks","Nonlinear systems","Backstepping","Robustness"
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems (ICCAS), 2015 15th International Conference on
ISSN :
2093-7121
Type :
conf
DOI :
10.1109/ICCAS.2015.7364748
Filename :
7364748
Link To Document :
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