Abstract
This work presents a scheme based on a discrete recurrent high order neural network identifier and a block control based on sliding modes for nonlinear discrete-time systems with input delays in real-time. The identifier is trained with an extended Kalman Filter based algorithm and the block control is used for trajectory tracking. Experimental results are included using a linear induction motor prototype with added delays to its input signals.
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Acknowledgments
The authors thank the support of CONACYT Mexico, through Projects CB256769 and CB258068 (“Project supported by Fondo Sectorial de Investigación para la Educación”).
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Rios, J.D., Alanís, A.Y., Arana-Daniel, N., López-Franco, C. (2018). Neural Identifier-Control Scheme for Nonlinear Discrete Systems with Input Delay. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_26
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DOI: https://doi.org/10.1007/978-3-319-67137-6_26
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