Ge Wei, Jie Wu, Xisheng Zhan, Bo Wu, Huaicheng Yan
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引用次数: 0
摘要
本文研究了有符号数字图下多代理系统(MAS)的双方格时变编队(BTVF)跟踪问题,其中领导者的输入是未知和有界的。提出了一种新型的 MAS 自适应非光滑 BTVF 跟踪协议,它不使用拉普拉卡矩阵的特征值。基于状态观测器,解决了系统状态不可测量的问题。此外,为了避免领导者非零输入引起的不希望的颤振,还提出了连续协议。在这种情况下,误差是均匀最终有界的。Lyapunov 方法反映了所提交协议的收敛性分析。最后,在多机器人系统上取得了理想的理论结果。
Observer‐based adaptive time‐varying bipartite formation tracking of multi‐agent systems with multiple nonautonomous leaders
In this article, the problem of bipartite time‐varying formation (BTVF) tracking for multi‐agent systems (MASs) under signed digraphs is investigated, in which the inputs of leaders are unknown and bounded. A novel kind of adaptive nonsmooth BTVF tracking protocol for MASs is proposed that did not utilize eigenvalue of Laplacian matrix. Based on the state observer, the problem that the system states are not measurable is solved. In addition, in order to avoid undesirable chattering caused by leaders' nonzero inputs, continuous protocols are proposed. And in this case, the error is uniformly ultimately bounded. Lyapunov method reflects the convergence analysis of the submitted protocols. At last, the desired theoretical results are achieved on a multirobot system.
期刊介绍:
The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application.
Published six times a year, the Journal aims to be a key platform for control communities throughout the world.
The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive.
Topics include:
The theory and design of control systems and components, encompassing:
Robust and distributed control using geometric, optimal, stochastic and nonlinear methods
Game theory and state estimation
Adaptive control, including neural networks, learning, parameter estimation
and system fault detection
Artificial intelligence, fuzzy and expert systems
Hierarchical and man-machine systems
All parts of systems engineering which consider the reliability of components and systems
Emerging application areas, such as:
Robotics
Mechatronics
Computers for computer-aided design, manufacturing, and control of
various industrial processes
Space vehicles and aircraft, ships, and traffic
Biomedical systems
National economies
Power systems
Agriculture
Natural resources.