Adaptive fuzzy control for a class of non-affine systems

Li, Xiaoqiang; Wang, Dan; Peng, Zhouhua; Sun, Gang

doi:10.1109/icicip.2010.5565234

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“…In [13] a robust adaptive fuzzy controller is presented for non-affine nonlinear system represented by input-output models. The Fuzzy logic and Nussbaum theory are utilized to fix the structured uncertainty of given system.…”

Section: Introductionmentioning

confidence: 99%

Wavelet neural network based controller design for non-affine nonlinear systems

Kumar¹,

Panwar²

2020

J. Math. Computer Sci.

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This paper addresses the design of wavelet neural network(WNN) based control scheme for non-affine nonlinear system with unknown control direction. Wavelet neural network is employed to approximate the uncertain part of control system. Since the learning capability of WNN is superior than any conventional NN for system identification. The update laws are derived from Lyapunov stability theory with Nussbaum technique so that all signals in closed loop system are stable and bounded. Finally, simulation example and analysis are provided to prove the effectiveness of controller.

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Section: Introductionmentioning

confidence: 99%