Asymptotic Backstepping Stabilization of SISO Nonlinear DAE Subsystems Using Artificial Neural Networks

Qiang Zang; Ying Zhou

doi:10.4028/www.scientific.net/AMM.325-326.1237

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 325-326Asymptotic Backstepping Stabilization of SISO...

Asymptotic Backstepping Stabilization of SISO Nonlinear DAE Subsystems Using Artificial Neural Networks

Abstract:

The problem of robust stabilization for a class of SISO uncertain nonlinear Differential-Algebraic Eqyatuion subsystems is considered in this paper. The robust stabilization controller is proposed based on backstepping approach using two-layer Artificial Neural Networks (ANN) whose weights are updated on-line. A new adaptive algorithm is proposed to update the weights of ANN such that all signals in the closed-loop systems are bounded and the states are convergent asymptotically to the equilibrium through the proposed controller.

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Periodical:

Applied Mechanics and Materials (Volumes 325-326)

Pages:

1237-1240

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.325-326.1237

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Online since:

June 2013

Authors:

Qiang Zang, Ying Zhou

Keywords:

Artificial Neural Network (ANN), Backstepping, DAE Systems, Subsystems

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References

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