DocumentCode :
260847
Title :
Tracking control for a class of uncertain nonlinear systems using Legendre Neural Network
Author :
Kulkarni, A. ; Gupta, V.
Author_Institution :
Medicaps Instt. of Tech. & Mgmt, Indore, India
fYear :
2014
fDate :
27-28 Feb. 2014
Firstpage :
1
Lastpage :
6
Abstract :
This work presents a Legendre Neural Network (LNN) based adaptive tacking controller for uncertain nonlinear systems. Due to the features of orthonormality, compact support and enhanced spectral response with increment in degree these polynomials posses promising function approximating capabilities. Proposed LNN utilizes the Legendre polynomial as activation function thereby improving the approximation capability of conventional feed forward neural network The effectiveness of LNN has been shown by considering the non linear system identification for an uncertain non linear dynamic system. The performance of the proposed network is found superior to that of a conventional neural network Adaptation laws are developed for the online tuning of the neural network parameters.
Keywords :
Legendre polynomials; adaptive control; function approximation; identification; neurocontrollers; nonlinear dynamical systems; transfer functions; uncertain systems; LNN based adaptive tacking controller; Legendre neural network based adaptive tacking controller; Legendre polynomial; activation function; feed forward neural network; function approximating capabilities; neural network adaptation laws; neural network parameter online tuning; nonlinear system identification; tracking control; uncertain nonlinear dynamic system; Artificial neural networks; Chebyshev approximation; Function approximation; Nonlinear systems; Polynomials; Artificial neural network (ANN); Legendre Polynomial; adaptive control; nonlinear function identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3835-3
Type :
conf
DOI :
10.1109/ICICES.2014.7033846
Filename :
7033846
Link To Document :
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