Key Laboratory of Nonlinear Mathematics Science, School of Mathematical Sciences, Fudan University, Shanghai, PR China.
Neural Netw. 2013 Oct;46:242-8. doi: 10.1016/j.neunet.2013.06.007. Epub 2013 Jun 20.
In this letter, we propose a new approach for the stability analysis of distributed continuous-time consensus algorithms in directed networks with time-dependent communication patterns. Instead of using a continuous-time Lyapunov function, we show how to analyze such a continuous-time algorithm by converting it to a discrete-time model. By using this method, we obtain a more general convergence result than existing ones. An example with numerical simulation is also provided to illustrate the theoretical results.
在这封信中，我们提出了一种新的方法，用于分析具有时变通信模式的有向网络中分布式连续时间一致性算法的稳定性。我们不是使用连续时间李雅普诺夫函数，而是展示了如何通过将连续时间算法转换为离散时间模型来分析这样的连续时间算法。通过使用这种方法，我们得到了比现有方法更一般的收敛结果。还提供了一个示例和数值模拟来说明理论结果。
