Abstract
The paper proposed a new fuzzy-neural recurrent multi-model for systems identification and states estimation of complex nonlinear mechanical plants with friction. The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive trajectory tracking control systems design. The designed local control laws are coordinated by a fuzzy rule based control system. The applicability of the proposed intelligent control system is confirmed by simulation and comparative experimental results, where a good convergent results, are obtained.
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Baruch, I.S., Beltran L, R., Olivares, JL., Garrido, R. (2004). A Fuzzy-Neural Multi-model for Mechanical Systems Identification and Control. In: Monroy, R., Arroyo-Figueroa, G., Sucar, L.E., Sossa, H. (eds) MICAI 2004: Advances in Artificial Intelligence. MICAI 2004. Lecture Notes in Computer Science(), vol 2972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24694-7_80
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DOI: https://doi.org/10.1007/978-3-540-24694-7_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21459-5
Online ISBN: 978-3-540-24694-7
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