State Feedback Stabilization of Large-Scale Logical Control Networks via Network Aggregation
Haitao Li, Yuna Liu, Shuling Wang, Ben Niu
Abstract
Finding a computationally tractable method to solve the feedback stabilization problem of large-scale logical control networks (LCNs) is a challenging issue. This article combines network aggregation and algebraic state-space representation (ASSR) to solve the state feedback stabilization problem of large-scale LCNs. First, the whole network of large-scale LCNs is divided into several small subnetworks via network aggregation. Second, the mode-dependent state feedback gain is explored for the stabilization of switched LCNs based on the ASSR method. Third, using the mode-dependent state feedback gain in each subnetwork, an effective result is proposed to design the state feedback gain for the stabilization of large-scale LCNs. Finally, two illustrative examples are given to demonstrate the effectiveness of the obtained new results.