Fault-Tolerant Time-Varying Formation Trajectory Tracking Control for Multi-Agent Systems with Time Delays and Semi-Markov Switching Topologies

被引:0
|
作者
Yu, Huangzhi [1 ]
Miao, Kunzhong [1 ]
He, Zhiqing [2 ]
Zhang, Hong [1 ]
Niu, Yifeng [1 ]
机构
[1] School of Intelligent Sciences, National University of Defense Technology, Changsha,410011, China
[2] Systems Engineering Research Institute, China State Shipbuilding Corporation Limited, Beijing,100094, China
基金
中国国家自然科学基金;
关键词
Adaptive control systems - Delay control systems - Feedback control - Markov processes - Risk assessment - Robustness (control systems) - State feedback - Stochastic control systems - Time varying control systems;
D O I
10.3390/drones8120778
中图分类号
学科分类号
摘要
The fault-tolerant time-varying formation (TVF) trajectory tracking control problem is investigated in this paper for uncertain multi-agent systems (MASs) with external disturbances subject to time delays under semi-Markov switching topologies. Firstly, based on the characteristics of actuator faults, a failure distribution model is established, which can better describe the occurrence of the failures in practice. Secondly, switching the network topologies is assumed to follow a semi-Markov stochastic process that depends on the sojourn time. Subsequently, a novel distributed state-feedback control protocol with time-varying delays is proposed to ensure that the MASs can maintain a desired formation configuration. To reduce the impact of disturbances imposed on the system, the (Formula presented.) performance index is introduced to enhance the robustness of the controller. Furthermore, by constructing an advanced Lyapunov–Krasovskii (LK) functional and utilizing the reciprocally convex combination theory, the TVF control problem can be transformed into an asymptotic stability issue, achieving the purpose of decoupling and reducing conservatism. Furthermore, sufficient conditions for system stability are obtained through linear matrix inequalities (LMIs). Eventually, the availability and superiority of the theoretical results are validated by three simulation examples. © 2024 by the authors.
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