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Adaptive Neural Network Model-based Event-triggered Attitude Tracking Control for Spacecraft

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Abstract

This article investigates the problem of attitude tracking control for spacecraft with limited communication, unknown system parameters, and external disturbances. An adaptive control scheme with an event-triggered mechanism (ETM) is proposed to alleviate the communication burden. Radial Basis Function Neural Network (RBFNN) estimation model is developed to provide the input signals for the control module in this control scheme. Estimated attitude information of the spacecraft generated from the estimation model will only be transmitted to the control module at the instants when the ETM is violated. The neural network (NN) and the estimation model will be updated complying with an adaptive algorithm at the discrete triggering instants. It’s substantiated that all the errors of attitude tracking converge towards corresponding residuals and there are no accumulated triggering instants. Numerical simulation also demonstrates the effectiveness of the proposed control method.

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Authors and Affiliations

  1. Research Center of Satellite Technology, Harbin Institute of Technology, Harbin, 150001, China

    Hongyi Xie, Baolin Wu & Weixing Liu

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  1. Hongyi Xie
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  2. Baolin Wu
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  3. Weixing Liu
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Corresponding author

Correspondence to Baolin Wu.

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Recommended by Associate Editor Choon Ki Ahn under the direction of Editor Chan Gook Park. This work was supported by the National Natural Science Foundation of China under Grant 61873312

Hongyi Xie received his B.Eng. degree in 2018 in the major of flight vehicle design and engineering from the Harbin Institute of Technology, Harbin, China, where he is currently pursuing a degree of master with the Research Center of Satellite Technology. His research interests are spacecraft attitude control and on-orbit services.

Baolin Wu received his B.Eng. and M.Eng. degrees in spacecraft design from the Harbin Institute of Technology, Harbin, China, in 2003 and 2005, respectively, and a Ph.D. degree in spacecraft formation control from Nanyang Technological University, Singapore, in 2011. From 2011 to 2013, he spent two years in the satellite research and development industry in ST Electronics (Satellite Systems) Pte Ltd., Singapore. He developed algorithms for satellite attitude determination and control system. He joined in Research Center of Satellite Technology, Harbin Institute of Technology in 2014. He is currently a full professor. His current research area is in spacecraft attitude control, attitude synchronization, spacecraft formation control, and trajectory optimization.

Weixing Liu received his B.Eng. and M.Eng. degrees in spacecraft design from the Harbin Institute of Technology, Harbin, China, in 2015 and 2017, respectively, where he is currently pursuing a Ph.D. degree with the Research Center of Satellite Technology. His research interests are spacecraft attitude control and on-orbit services.

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Xie, H., Wu, B. & Liu, W. Adaptive Neural Network Model-based Event-triggered Attitude Tracking Control for Spacecraft. Int. J. Control Autom. Syst. 19, 172–185 (2021). https://doi.org/10.1007/s12555-019-0487-5

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  • DOI: https://doi.org/10.1007/s12555-019-0487-5

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