Abstract
An scheme of composite sliding control is proposed for a class of uncertainty nonlinear system, which is based on fuzzy neural networks (FNN) and simple neural networks (SNN). The SNN is uniquely determined by the design of the global integral sliding mode surface, the output of which replaces the corrective control, and FNN is applied to mimic the equivalent control. In this scheme, the bounds of the uncertainties and the extern disturbance are not required to be known in advance, and the stability of systems is analyzed based on Lyapunov function. Simulation results are given to demonstrate the effectiveness of this scheme. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Hao, Y., Zhang, J., & Chen, Z. (2007). Adaptive global integral neuro-sliding mode control for a class of nonlinear system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4491 LNCS, pp. 102–111). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_14
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