Wavelet Functions Performances in Intelligent Direct Adaptive Control of Uncertain Nonlinear Systems

被引：0
|
作者：
Kahili, Kheira [1 ]
Bouhali, Omar [1 ]
Rizoug, Nassim [2 ]
机构：
[1] Univ Mohamed Seddik Benyahia, Lab MecaTron LMT, Jijel, Algeria
[2] ESTACA Sch, Lab Mecatron, Laval, France
来源：
PROCEEDINGS 2018 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL SCIENCES AND TECHNOLOGIES IN MAGHREB (CISTEM) | 2018年
关键词：
wavelet neural networks; activation functions; performance comparison; direct adaptive control; NEURAL-NETWORK; MODELS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, a comparative study of wavelet functions performances in intelligent direct adaptive control is developed. The main idea is to investigate and compare the tracking accuracy of different wavelet activation functions in intelligent control of uncertain nonlinear systems. The most commonly used wavelet families such as Mexican hat, Morlet and Gaussian wavelet are subject of this study. Lyapunov's direct method is used to prove the stability and to derive the Wavelet Neural Networks (WNNs) parameters adaptation laws. The simulation results are presented to classify the wavelet functions under study.
引用
收藏
页码：266 / 271
页数：6
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