Hierarchical Hybrid Control for Scaled Consensus and Its Application to Secondary Control for DC Microgrid
Shuangye Mo, Wu‐Hua Chen, Xiaomei Lu
Abstract
This article addresses the scaled consensus problem for a class of heterogeneous multiagent systems (MASs) with a cascade-type two-layer structure. It is assumed that the information of the upper layer state components is intermittently exchangeable through a strongly connected communication network among the agents. A distributed hierarchical hybrid control framework is proposed, which consists of a lower layer controller and an upper layer one. The lower layer controller is a decentralized continuous feedback controller, which makes the lower layer state components converge to their target values. The upper layer controller is a distributed impulsive controller, which enforces a scaled consensus for the upper layer state components. It is proved that the two layer controllers can be designed separately. By considering the dwell-time condition of impulses and the feature of the strongly connected Laplacian matrix, a novel weighted discontinuous function is constructed for scaled consensus analysis. By using the Lyapunov function, a sufficient condition for scaled consensus of the MAS is derived in terms of linear matrix inequalities. As an application of the proposed distributed hybrid control strategy, a relaxed distributed hybrid secondary control algorithm for dc microgrid is obtained, by which the balance requirement on the communication digraph is removed, and an improved current sharing condition is obtained.