@inproceedings{e1cdb87c596b4235a7fa362e948cc161,
title = "Adaptive backstepping tracking control using self-organizing fuzzy neural network",
abstract = "This paper proposes an adaptive backstepping tracking control (ABTC) via self-organizing fuzzy neural network (SOFNN) approach. The proposed ABTC system is comprised of a backstepping tracking controller and an L1 controller. The backstepping tracking controller containing a SOFNN identifier is the principal controller, and the L, controller is designed to achieve a tracking performance with desired attenuation level. The SOFNN identifier is used to online estimate the system dynamics with structure and parameter learning. Finally, the proposed ABTC is applied to control a chaotic dynamic system. The simulation results verify that the proposed ABTC system can achieve favorable tracking performance by incorporating of neural network approach and adaptive backstepping control technique.",
keywords = "Adaptive control, Backstepping control, Robust control, Rule elimination, Rule generation",
author = "Lin, {Chih Min} and Hsu, {Chun Fei} and Chung, {I. Fang}",
year = "2006",
month = jun,
language = "English",
isbn = "9789889867133",
series = "Lecture Notes in Engineering and Computer Science",
pages = "54--59",
booktitle = "IMECS 2006 - International MultiConference of Engineers and Computer Scientists 2006",
note = "null ; Conference date: 20-06-2006 Through 22-06-2006",
}