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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Published in | 2011 Third International Conference on Measuring Technology and Mechatronics Automation Vol. 2; pp. 160 - 162 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.01.2011
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Subjects | |
Online Access | Get full text |
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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. |
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ISBN: | 1424490103 9781424490103 |
ISSN: | 2157-1473 |
DOI: | 10.1109/ICMTMA.2011.327 |