IEEE Trans Neural Netw Learn Syst. 2018 May;29(5):1514-1524. doi: 10.1109/TNNLS.2017.2673020. Epub 2017 Mar 14.
This paper investigates the data-driven consensus tracking problem for multiagent systems with both fixed communication topology and switching topology by utilizing a distributed model free adaptive control (MFAC) method. Here, agent's dynamics are described by unknown nonlinear systems and only a subset of followers can access the desired trajectory. The dynamical linearization technique is applied to each agent based on the pseudo partial derivative, and then, a distributed MFAC algorithm is proposed to ensure that all agents can track the desired trajectory. It is shown that the consensus error can be reduced for both time invariable and time varying desired trajectories. The main feature of this design is that consensus tracking can be achieved using only input-output data of each agent. The effectiveness of the proposed design is verified by simulation examples.
本文利用一种分布式无模型自适应控制（MFAC）方法，研究了具有固定通信拓扑和切换拓扑的多智能体系统的数据驱动一致性跟踪问题。这里，智能体的动力学由未知的非线性系统描述，并且只有部分跟随者可以访问期望轨迹。基于伪偏导数，对每个智能体应用动力线性化技术，然后提出一种分布式 MFAC 算法，以确保所有智能体都能跟踪期望轨迹。结果表明，对于时不变和时变期望轨迹，共识误差都可以减小。该设计的主要特点是仅使用每个智能体的输入输出数据即可实现一致性跟踪。通过仿真示例验证了所提出设计的有效性。
