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Neuro-Fuzzy Network Based Adaptive Tracking Controller for a Nonlinear System | ||
| Basrah Journal for Engineering Science | ||
| Article 9, Volume 17, Issue 1, 2017, Pages 70-75 PDF (0 K) | ||
| Author | ||
| Abdul-Basset A. Al-Hussein | ||
| Abstract | ||
| In this paper, a neuro-fuzzy network-based adaptive tracking controller is suggested for controlling a type of nonlinear system. Where two neuro-fuzzy networks have been used to learn the system dynamics uncertainty bounds by using Lyapunov method. Then the output of these two networks is used to build a sliding mode controller. The stability of the control system is proved and stable neuro-fuzzy controller parameters adjustment laws are selected using Lyapunov theory. The simulation case study shows that the controlled system tracking the reference model effectively with smooth control effort and robust performance has been achieved | ||
| Keywords | ||
| Neuro; Fuzzy network; Adaptive Control; Model Reference Control; Uncertain Dynamics; Sliding Mode Controller | ||
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