Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction |
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| Authors: | Mohammad M Arefi Jafar Zarei Hamid R Karimi |
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| Institution: | 1. Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, 71348-51154 Shiraz, Iran;2. Department Control Engineering, School of Electrical and Electronics Engineering, Shiraz University of Technology, 71557-13876 Shiraz, Iran;3. Department of Engineering, Faculty of Engineering and Science, University of Agder, N-4898 Grimstad, Norway |
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| 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. |
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| Keywords: | Observer-based control Uncertain non-affine systems Unknown gain direction Neural network control |
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