School of Automation and Electrical Engineering, Zhejiang University of Science & Technology, Hangzhou, China.
PLoS One. 2022 Nov 10;17(11):e0274461. doi: 10.1371/journal.pone.0274461. eCollection 2022.
This paper is concerned with the sampled-data consensus of networked Euler-Lagrange systems. The Euler-Lagrange system has enormous advantages in analyzing and designing dynamical systems. Yet, some problems arise in the Euler-Lagrange equation-based control laws when they contain sampled-data feedbacks. The control law differentiates the discontinuous sampled-data signals to generate its control input. In this process, infinities in the control inputs are generated inevitably. The main goal of this work is to eliminate these infinities and make the control inputs applicable. To reach this goal, a class of differentiable pulse functions is designed for the controllers. The pulse functions work as multipliers on the sampled-data signals to make them differentiable, hence avoid the infinities. A new consensus condition compatible with the pulse function is also obtained through rigorous consensus analysis. The condition is proved to be less conservative compared with that of the existing method. Finally, numerical examples are given to illustrate the findings and theoretical results.
本文研究了基于网络的 Euler-Lagrange 系统的采样数据一致性问题。Euler-Lagrange 系统在分析和设计动力学系统方面具有巨大的优势。然而，基于 Euler-Lagrange 方程的控制律在包含采样数据反馈时会出现一些问题。该控制律通过对不连续的采样数据信号进行微分来生成其控制输入。在这个过程中，控制输入不可避免地会产生无穷大。这项工作的主要目标是消除这些无穷大，并使控制输入可用。为了达到这个目标，为控制器设计了一类可微分的脉冲函数。脉冲函数作为采样数据信号的乘法器，使它们可微，从而避免了无穷大。通过严格的一致性分析，还获得了与脉冲函数兼容的新一致性条件。该条件与现有方法相比，证明具有更小的保守性。最后，给出了数值示例来说明研究结果和理论结果。
