Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter

Kun Yan, Hongtian Chen, Chaobo Chen*, Song Gao, Jingliang Sun

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

In this paper, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time-varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti-disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme.

源语言英语
页(从-至)1-11
页数11
期刊ISA Transactions
148
DOI
出版状态已出版 - 5月 2024

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