Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-08
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
An adaptive sliding controller using radial basis function (RBF) network to approximate the unknown system dynamics microelectromechanical systems (MEMS) gyroscope sensor is proposed.
Neural controller is proposed to approximate the unknown system model and sliding controller is employed to eliminate the approximation error and attenuate the model uncertainties and external disturbances.
Online neural network (NN) weight tuning algorithms, including correction terms, are designed based on Lyapunov stability theory, which can guarantee bounded tracking errors as well as bounded NN weights.
The tracking error bound can be made arbitrarily small by increasing a certain feedback gain.
Numerical simulation for a MEMS angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive neural control scheme and demonstrate the satisfactory tracking performance and robustness.
American Psychological Association (APA)
Yang, Yuzheng& Fei, Juntao. 2014. Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-450524
Modern Language Association (MLA)
Yang, Yuzheng& Fei, Juntao. Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation. Journal of Applied Mathematics No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-450524
American Medical Association (AMA)
Yang, Yuzheng& Fei, Juntao. Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-450524
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-450524