Record number :
1545218
Title of article :
Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction
Author/Authors :
Arefi، نويسنده , , Mohammad M. and Zarei، نويسنده , , Jafar and Karimi، نويسنده , , Hamid R.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Pages :
15
From page :
4302
To page :
4316
Abstract :
This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. The proposed controller is designed based on strict-positive-real (SPR) Lyapunov stability theory to ensure the asymptotic stability of the closed-loop system. Finally, two simulation studies are presented to demonstrate the effectiveness of the developed scheme.
Keywords :
Observer-based control , Neural Network Control , Unknown gain direction , Uncertain non-affine systems
Journal title :
Journal of the Franklin Institute
Serial Year :
2014
Link To Document :
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