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ע⣺ՓڡϵycӼg2008,30(4):723-726l
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(A|WԄӻϵ, Ϻ 200237)

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ЈD̖: TP 273 īI־a: A

Adaptive neural network variable structure control for a class of non-afine nonlinear pure-feedback systems

DU Hong-bin, LI Shao-jun
( Dept. of Automation, East China Univ. of Science & Technology , Shanghai 200237 , China)

Abstract :A class of nonlinear non-affine pure-feedback SISO systems with unknown nonlinear func tions are investigated. An adaptive variable structure control is presented for this class of systems based on the combination of mean value theorem, neural network parameterization, and decoupled ackstepping design. All the signals in the closed-loop system can be shown to be semi-globally uniformly ultimate boundedness around the equilibrium point. The effectiveness of the proposed control law is verified via simulation for a non-affine CSTR plant.
Keywords : nonlinear; adaptive variable structure control; neural network parameterization; pure-feedback systems

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