Exponential Fast Terminal Sliding Mode Control

A new learning algorithm for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions is proposed. The concept of exponential fast terminal sliding mode is introduced into the learning algorithm to improve approximation ability. The Lyapunov stability analysis guarant...

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Bibliographic Details
Published in2011 Third International Conference on Measuring Technology and Mechatronics Automation Vol. 2; pp. 160 - 162
Main Authors He Naibao, Jiang Changsheng, Gao Qian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2011
Subjects
adaptive control
Approximation algorithms
Approximation methods
Artificial neural networks
Fuzzy control
Fuzzy neural networks
Nonlinear systems
slide control
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Summary:A new learning algorithm for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions is proposed. The concept of exponential fast terminal sliding mode is introduced into the learning algorithm to improve approximation ability. The Lyapunov stability analysis guarantees that the approximation is stable and converges to the unknown function with improved speed. The proposed FNN approximator is then applied in the control of an unstable nonlinear system. Simulation results demonstrate that the proposed method can obtain good approximation ability and tracing control of nonlinear dynamic system.
ISBN:1424490103
9781424490103
ISSN:2157-1473
DOI:10.1109/ICMTMA.2011.327