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.
Sponsored by Shanxi Nature Science Foundation(20041049).
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Hao, Y., Zhang, J., Chen, Z. (2007). Adaptive Global Integral Neuro-sliding Mode Control for a Class of Nonlinear System. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_14
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DOI: https://doi.org/10.1007/978-3-540-72383-7_14
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