Adaptive Neural Control of Switched Nonlinear StochasticSystem with Time-Varying Delay Based on ELM

XIAO Yang; LONG Fei

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Adaptive Neural Control of Switched Nonlinear StochasticSystem with Time-Varying Delay Based on ELM

XIAO Yang 1,LONG Fei 2 * #

1.College of Computer Science and Information, Guizhou University, GuiYang 550025

2.College of Computer Science and Information, Guizhou University, Guiyang 550025, P. R. China

*Correspondence author

#Submitted by

Subject:

Funding: Doctor’s foundation of Higher Education （No.No. 20105201120003）

Opened online:23 July 2012

Accepted by: none

Citation: XIAO Yang,LONG Fei.Adaptive Neural Control of Switched Nonlinear StochasticSystem with Time-Varying Delay Based on ELM[OL]. [23 July 2012] http://en.paper.edu.cn/en_releasepaper/content/4484820

The paper presents a adaptive neural networks control scheme without system observers for a class of SISO stochastic nonlinear switched systems with time-varying delay. In the scheme, only a single hidden layer feedforward network (SLFN) is employed to compensate for all known system nonlinear terms depending on the delayed output. The output weights are updated based on the Lyapunov synthesis approach and backstepping technique to guarantee the stability of the overall system. Then a special switching law are given based on attenuation speed of each subsystem. Different from the existing techniques, the parameters of the SLFN are adjusted based on a new neural networks learning algorithm named as extreme learning machine (ELM), where all the hidden node parameters randomly be generated. Finally, the proposed AANC scheme is applied to an example and the simulation results demonstrate the effectiveness of the control schem.

Keywords:Stochastic switched nonlinear systems; Backstepping; ELM; Adaptive neural network control

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