Abstract
This work addresses the robust neural direct control of hypersonics flight vehicle (HFV) under dynamics uncertainty and actuator saturation. The controller is constructed with robust control and neural control. To deal with the actuator saturation, a Gaussian error function is employed to express the effect. The dynamic surface control (DSC) is studied to remove the explosion of the complexity by using a nonlinear adaptive filter. The simulation tested on the hypersonic vehicle control-oriented model (COM) shows the effectiveness of the control design.
This work was supported by Science and Technology on Space Intelligent Control Laboratory (ZDSYS-2017-05), National Natural Science Foundation of China (Grant Nos: 61622308, 61873206, 61673341), the Fundamental Research Funds of Shenzhen Science and Technology Project (JCYJ20160229172341417) and the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. ICT1800421, ICT1900312).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Xu, B., Shi, Z.K.: An overview on flight dynamics and control approaches for hypersonic vehicles. Sci. China Inf. Sci. 58(7), 1–19 (2015)
Chen, M., Tao, G., Jiang, B.: Dynamic surface control using neural networks for a class of uncertain nonlinear systems with input saturation. IEEE Trans. Neural Netw. Learn. Syst. 26(9), 2086–2097 (2015)
Parker, J.T., Serrani, A., Yurkovich, S., et al.: Control-oriented modeling of an air-breathing hypersonic vehicle. J. Guidance Control Dyn. 30(3), 856–869 (2007)
Farrell, J.A., Polycarpou, M., Sharma, M., et al.: Command filtered backstepping. IEEE Trans. Autom. Control 54(6), 1391–1395 (2009)
Swaroop, D., Hedrick, J.K., Yip, P.P., et al.: Dynamic surface control for a class of nonlinear systems. IEEE Trans. Autom. Control 45(10), 1893–1899 (2000)
Liu, Y.H.: Dynamic surface asymptotic tracking of a class of uncertain nonlinear hysteretic systems using adaptive filters. J. Franklin Inst. 355(1), 123–140 (2018)
Chen, W., Jiao, L.C., Wu, J.: Globally stable adaptive robust tracking control using RBF neural networks as feedforward compensators. Neural Comput. Appl. 21(2), 351–363 (2012)
Chen, W., Ge, S.S., Wu, J., et al.: Globally stable adaptive backstepping neural network control for uncertain strict-feedback systems with tracking accuracy known a priori. IEEE Trans. Neural Netw. Learn. Syst. 26(9), 1842–1854 (2015)
Huang, J.T.: Global tracking control of strict-feedback systems using neural networks. IEEE Trans. Neural Netw. Learn. Syst. 23(11), 1714–1725 (2012)
Xu, B., Yang, C., Pan, Y.: Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle. IEEE Trans. Neural Netw. Learn. Syst. 26(10), 2563–2575 (2015)
Xu, B., Yang, D., Shi, Z., et al.: Online recorded data-based composite neural control of strict-feedback systems with application to hypersonic flight dynamics. IEEE Trans. Neural Netw. Learn. Syst. 29(8), 3839–3849 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wang, X., Xu, B., Zhang, P., Zhang, Y. (2019). Robust Neural Direct Hypersonic Flight Control Under Actuator Saturation. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-7986-4_36
Download citation
DOI: https://doi.org/10.1007/978-981-13-7986-4_36
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-7985-7
Online ISBN: 978-981-13-7986-4
eBook Packages: Computer ScienceComputer Science (R0)