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Article

An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform

1
School of Instrumentation Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China
2
Beijing Institute of Control & Electronic Technology, Beijing 100038, China
*
Author to whom correspondence should be addressed.
Academic Editor: Gert F. Trommer
Sensors 2017, 17(5), 978; https://doi.org/10.3390/s17050978
Received: 10 January 2017 / Revised: 5 April 2017 / Accepted: 25 April 2017 / Published: 28 April 2017
(This article belongs to the Section Physical Sensors)
The mobile satcom antenna (MSA) enables a moving vehicle to communicate with a geostationary Earth orbit satellite. To realize continuous communication, the MSA should be aligned with the satellite in both sight and polarization all the time. Because of coupling effects, unknown disturbances, sensor noises and unmodeled dynamics existing in the system, the control system should have a strong adaptability. The significant features of terminal sliding mode control method are robustness and finite time convergence, but the robustness is related to the large switching control gain which is determined by uncertain issues and can lead to chattering phenomena. Neural networks can reduce the chattering and approximate nonlinear issues. In this work, a novel B-spline curve-based B-spline neural network (BSNN) is developed. The improved BSNN has the capability of shape changing and self-adaption. In addition, the output of the proposed BSNN is applied to approximate the nonlinear function in the system. The results of simulations and experiments are also compared with those of PID method, non-singularity fast terminal sliding mode (NFTSM) control and radial basis function (RBF) neural network-based NFTSM. It is shown that the proposed method has the best performance, with reliable control precision. View Full-Text
Keywords: mobile satcom antenna; inertial sensor; stabilized platform; B-spline neural network; terminal sliding mode (TSM) mobile satcom antenna; inertial sensor; stabilized platform; B-spline neural network; terminal sliding mode (TSM)
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MDPI and ACS Style

Zhang, X.; Zhao, Y.; Guo, K.; Li, G.; Deng, N. An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform. Sensors 2017, 17, 978. https://doi.org/10.3390/s17050978

AMA Style

Zhang X, Zhao Y, Guo K, Li G, Deng N. An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform. Sensors. 2017; 17(5):978. https://doi.org/10.3390/s17050978

Chicago/Turabian Style

Zhang, Xiaolei, Yan Zhao, Kai Guo, Gaoliang Li, and Nianmao Deng. 2017. "An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform" Sensors 17, no. 5: 978. https://doi.org/10.3390/s17050978

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