State Feedback Stabilization of Large-Scale Logical Control Networks via Network Aggregation

• 成果类型: Article
• 署名作者: Li, Haitao; Liu, Yuna; Wang, Shuling; Niu, Ben
• 署名单位: Shandong Normal University; Shandong Normal University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3057139
• 发表日期: 2021
• 页码: 6033-6040
• 关键词: State feedback; Aerospace electronics; Partitioning algorithms; genetics; control design; computational modeling; Biological system modeling; Algebraic state-space representation (ASSR); logical control network (LCN); mode-dependent control; network aggregation; stabilization

摘要

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.