Reaching Non-Negative Edge Consensus of Networked Dynamical Systems
研究了无向网络化线性时不变系统的非负边共识问题，为每条边关联状态变量并设计分布式算法，利用线性规划和低增益反馈简化反馈增益矩阵设计，适用于输入饱和情形。
In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.