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

Volume 24, Issue 1, pp 49--58 http://dx.doi.org/10.22436/jmcs.024.01.05

Publication Date: December 23, 2020 Submission Date: September 05, 2020 Revision Date: September 26, 2020 Accteptance Date: November 14, 2020

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Authors

Pramendra Kumar - Department of Applied Mathematics, Gautam Buddha University, India. Vikas Panwar - Department of Applied Mathematics, Gautam Buddha University, India.

Abstract

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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Keywords

• Non-affine Nonlinear system
• Lyapunov stability theory
• wavelet neural network
• Nussbaum function

MSC

•  34D08
•  93D05

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