Abstract
A new learning algorithm for fuzzy system to approximate unknown nonlinear continuous functions is presented. Fast terminal sliding mode combining the finite time convergent property of terminal attractor and exponential convergent property of linear system is introduced into the conventional back-propagation 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 fuzzy approximator is then applied in the control of an unstable nonlinear system. Simulation results demonstrate that the proposed method is better than conventional method in approximation and tracing control of nonlinear dynamic system.
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© 2006 Springer-Verlag Berlin Heidelberg
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Liu, Y., Cao, F., Peng, Y., Yang, X., Miao, D. (2006). A Novel Fuzzy Approximator with Fast Terminal Sliding Mode and Its Application. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_20
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DOI: https://doi.org/10.1007/11881599_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45916-3
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