Zhang Xianglin, Luo Mingqiang, Guo Simeng, Cui Zhiyang
School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
Biomimetics (Basel). 2024 Mar 10;9(3):167. doi: 10.3390/biomimetics9030167.
In this paper, we explore a nonlinear interactive network system comprising nodalized flapping-wing micro air vehicles (FMAVs) to address the distributed H∞ state estimation problem associated with FMAVs. We enhance the model by introducing an information fusion function, leading to an information-fusionized estimator model. This model ensures both estimation accuracy and the completeness of FMAV topological information within a unified framework. To facilitate the analysis, each FMAV's received signal is individually sampled using independent and time-varying samplers. Transforming the received signals into equivalent bounded time-varying delays through the input delay method yields a more manageable and analyzable time-varying nonlinear network error system. Subsequently, we construct a Lyapunov-Krasovskii functional (LKF) and integrate it with the refined Wirtinger and relaxed integral inequalities to derive design conditions for the FMAVs' distributed H∞ state estimator, minimizing conservatism. Finally, we validate the effectiveness and superiority of the designed estimator through simulations.
在本文中，我们探索了一种由节点化扑翼微型飞行器（FMAV）组成的非线性交互网络系统，以解决与FMAV相关的分布式H∞状态估计问题。我们通过引入信息融合函数来增强模型，从而得到一个信息融合估计器模型。该模型在统一框架内确保了估计精度和FMAV拓扑信息的完整性。为便于分析，使用独立且时变的采样器对每个FMAV接收到的信号进行单独采样。通过输入延迟方法将接收到的信号转换为等效有界时变延迟，得到一个更易于管理和分析的时变非线性网络误差系统。随后，我们构造了一个李雅普诺夫 - 克拉索夫斯基泛函（LKF），并将其与改进的Wirtinger不等式和松弛积分不等式相结合，以推导FMAV分布式H∞状态估计器的设计条件，从而使保守性最小化。最后，我们通过仿真验证了所设计估计器的有效性和优越性。
