@inproceedings{b15aa0fe64ad4d728120480becb8a890,
title = "Adaptive Parameter Estimation Control Based on Back-Stepping for UAV",
abstract = "An adaptive parameter estimation control approach is proposed for the longitudinal control of unmanned aerial vehicle (UAV). The system model is written as the linearly-parameterized form. A novel parameter estimation framework with back-stepping technique is introduced to estimate the model parameters online. The parameter error information is derived by two different ways: auxiliary filtered variables and serial-parallel estimation model, which guarantees exponential error convergence. Besides, the first order tracking differentiator is utilized to get differentiation of virtual controller signal at each step, to avoid the problem of “explosion of complexity”. Stability analysis by Lyapunov method proves that closed-loop system achieves uniform ultimately bounded stability. Finally, A numerical simulation example is provided to validate the effectiveness of the proposed control approach.",
keywords = "Adaptive control, Back-stepping, Parameter estimation, UAV",
author = "Zhihui Du and Jingping Shi and Zhonghua Wu and Jingchao Lu",
note = "Publisher Copyright: {\textcopyright} 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2020 ; Conference date: 23-10-2020 Through 25-10-2020",
year = "2022",
doi = "10.1007/978-981-15-8155-7_154",
language = "英语",
isbn = "9789811581540",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1829--1843",
editor = "Liang Yan and Haibin Duan and Xiang Yu",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020",
}