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Erschienen in:
Tracking Control for Unknown Nonlinear System Based on Augmented Matrix Algorithm Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Hopfield Neural Network Identification and Adaptive Control for Bouc–Wen Hysteresis System

verfasst von : Gao Xuehui, Sun Bo, Zhang Chengyuan

Erschienen in: Innovative Techniques and Applications of Modelling, Identification and Control

Verlag: Springer Singapore

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Abstract

An adaptive controller is proposed for hysteresis nonlinear systems where the coefficients were estimated by Hopfield Neural Network (HNN). First, a Bouc–Wen model is applied to describe the hysteresis nonlinearity. Then, a nonlinear system model is employed with the unknown parameters of the state-space equation and a new HNN is designed to identify the coefficients. Finally, an adaptive controller is proposed and the stability is guaranteed by a Lyapunov function candidate. Simulation results verify the effectiveness of the proposed identification and adaptive control approach.

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Vorheriges Kapitel An Improved Online Denoising Algorithm Based on the Adaptive Noise Covariance
Nächstes Kapitel Harmonics Elimination in Permanent Magnet Synchronous Generator with Current Injection at DC Side
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Metadaten
Titel
Hopfield Neural Network Identification and Adaptive Control for Bouc–Wen Hysteresis System
verfasst von
Gao Xuehui
Sun Bo
Zhang Chengyuan
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Innovative Techniques and Applications of Modelling, Identification and Control

Print ISBN: 978-981-10-7211-6

Electronic ISBN: 978-981-10-7212-3

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-7212-3_9

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