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基于干扰观测器和无碰撞的无人水面舰艇神经自适应约束控制

Neuro-adaptive containment control of unmanned surface vehicles with disturbance observer and collision-free.

作者信息

Deng Qun, Peng Yan, Qu Dong, Han Tao, Zhan Xisheng

机构信息

The School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, 200444, China.

The School of Mechatronics and Control Engineering, Hubei Normal University, Huangshi, Hubei, 435002, China.

出版信息

ISA Trans. 2022 Oct;129(Pt A):150-156. doi: 10.1016/j.isatra.2022.01.004. Epub 2022 Jan 10.

DOI:10.1016/j.isatra.2022.01.004
PMID:35181004
Abstract

The adaptive containment control problem with collision avoidance is investigated for unmanned surface vehicles (USVs). At first, the finite time disturbance observer is developed to present the estimation and compensation of external disturbance. Then, incorporating the artificial potential and radial basis function into the new containment strategy, all followers can enter the convex hull spanned by leaders while the collision is avoided. Furthermore, it is demonstrated that the error signals in the closed-loop system are boundedness by employing Lyapunov stability. Simulation studies finally manifest the effectiveness of proposed method.

摘要

针对无人水面舰艇(USV),研究了具有避碰功能的自适应包容控制问题。首先,开发了有限时间干扰观测器,用于估计和补偿外部干扰。然后,将人工势场和径向基函数纳入新的包容策略,所有跟随者都能在避免碰撞的同时进入由领导者所构成的凸包。此外,通过利用李雅普诺夫稳定性证明了闭环系统中的误差信号是有界的。仿真研究最终表明了所提方法的有效性。

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