Suppr超能文献

用于智慧城市安全观测的两层网络化无人飞艇分布式分数阶智能自适应容错编队-包容控制

Distributed Fractional-Order Intelligent Adaptive Fault-Tolerant Formation-Containment Control of Two-Layer Networked Unmanned Airships for Safe Observation of a Smart City.

作者信息

Yu Ziquan, Zhang Youmin, Jiang Bin, Su Chun-Yi, Fu Jun, Jin Ying, Chai Tianyou

出版信息

IEEE Trans Cybern. 2022 Sep;52(9):9132-9144. doi: 10.1109/TCYB.2021.3052875. Epub 2022 Aug 18.

Abstract

This article investigates a distributed fractional-order fault-tolerant formation-containment control (FOFTFCC) scheme for networked unmanned airships (UAs) to achieve safe observation of a smart city. In the proposed control method, an interval type-2 fuzzy neural network (IT2FNN) is first developed for each UA to approximate the unknown term associated with the loss-of-effectiveness faults in the distributed error dynamics, and then a disturbance observer (DO) is proposed to compensate for the approximation error and bias fault encountered by each UA, such that the composite learning strategy composed of the IT2FNN and the DO is obtained for each UA. Moreover, fractional-order (FO) calculus is incorporated into the control scheme to provide an extra degree of freedom for the parameter adjustments. The salient feature of the proposed control scheme is that the composite learning algorithm and FO calculus are integrated to achieve a satisfactory fault-tolerant formation-containment control performance even when a portion of leader/follower UAs is subjected to the actuator faults in a distributed communication network. Furthermore, it is shown by Lyapunov stability analysis that all leader UAs can track the virtual leader UA with time-varying offset vectors, and all follower UAs can converge into the convex hull spanned by the leader UAs. Finally, comparative hardware-in-the-loop (HIL) experimental results are presented to show the effectiveness and superiority of the proposed method.

摘要

本文研究了一种用于网络无人飞艇(UA)的分布式分数阶容错编队-包容控制(FOFTFCC)方案,以实现对智慧城市的安全观测。在所提出的控制方法中,首先为每个UA开发了一个区间二型模糊神经网络(IT2FNN),用于逼近分布式误差动态中与有效性丧失故障相关的未知项,然后提出了一个干扰观测器(DO)来补偿每个UA遇到的逼近误差和偏差故障,从而为每个UA获得由IT2FNN和DO组成的复合学习策略。此外,分数阶(FO)微积分被纳入控制方案,为参数调整提供额外的自由度。所提出的控制方案的显著特点是,即使在分布式通信网络中的一部分领导者/跟随者UA受到执行器故障影响时,复合学习算法和FO微积分也被集成起来,以实现令人满意的容错编队-包容控制性能。此外,通过李雅普诺夫稳定性分析表明,所有领导者UA都可以通过时变偏移向量跟踪虚拟领导者UA,并且所有跟随者UA都可以收敛到由领导者UA跨越的凸包内。最后,给出了比较性的硬件在环(HIL)实验结果,以证明所提方法的有效性和优越性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验