Abstract
This paper presents a nonlinear controller for uncertain single-input–single-output (SISO) nonlinear systems. The adopted approach is based on the feedback linearization strategy and enhanced by a Radial Basis Function neural network to cope with modeling inaccuracies and external disturbances that can arise. An application of this nonlinear controller to an electro-hydraulic actuated system subject to an unknown dead-zone input is also presented. The obtained numerical results demonstrate the improved control system performance.
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Fernandes, J.M.M., Tanaka, M.C., Freire Júnior, R.C.S., Bessa, W.M. (2012). Feedback Linearization with a Neural Network Based Compensation Scheme. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_72
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DOI: https://doi.org/10.1007/978-3-642-32639-4_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32638-7
Online ISBN: 978-3-642-32639-4
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