BISIMULATIONS OF BOOLEAN CONTROL NETWORKS

被引:26
|
作者
Li, Rui [1 ]
Chu, Tianguang [2 ]
Wang, Xingyuan [3 ]
机构
[1] Dalian Univ Technol, Sch Math Sci, Dalian 116024, Peoples R China
[2] Peking Univ, Coll Engn, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
[3] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Boolean control network; bisimulation; simulation; controllability; stabilizability; synchronization; NP-hardness; NONLINEAR CONTROL-SYSTEMS; FEEDBACK STABILIZATION; SIMULATION RELATIONS; REGULATORY NETWORK; OBSERVABILITY; MODEL; SYNCHRONIZATION; CONTROLLABILITY; STABILITY; DESIGN;
D O I
10.1137/17M1117331
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A framework for analyzing bisimulation relations of Boolean control networks (BCNs) is set up in this paper. Bisimulation relations are natural objectives in control systems theory: A bisimulation relation between a pair of control systems defines a relation on their state spaces or state sets explaining how a trajectory or transition of one system can be paired with a trajectory or transition of the other system, and vice versa. The paper first formalizes the notion of (bi)simulation in BCNs and presents detailed results characterizing (bi)simulation relations for BCNs. Then, as an application of the notion of bisimulation, it considers the propagation of the fundamental properties of (macro)controllability and stabilizability through a bisimulation relation. It thereby suggests the possibility that certain control properties of a BCN can be inferred by analyzing a potentially simpler BCN. The analysis developed in this paper is based on the semitensor product approach, which gives algorithms that have exponential time complexity. A question that naturally arises is if it is possible to check bisimulation relations for BCNs in polynomial time. This question is answered in the negative, by proving that the problem of deciding whether a relation between BCNs is a bisimulation relation is NP-hard.
引用
收藏
页码:388 / 416
页数:29
相关论文
共 50 条
  • [1] BISIMULATIONS OF PROBABILISTIC BOOLEAN NETWORKS
    LI, R. U. I.
    Zhang, Q., I
    Chu, T. I. A. N. G. U. A. N. G.
    [J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2022, 60 (05) : 2631 - 2657
  • [2] Bisimulations for delayed switched Boolean control networks and its application in controllability
    Yu, Weiyong
    Deng, Zhenhua
    Guo, Qianjin
    Liu, Qiang
    [J]. IET CONTROL THEORY AND APPLICATIONS, 2023, 17 (11): : 1552 - 1565
  • [3] Bisimulations of boolean control networks with impulsive effects and its application in controllability
    Zhang, Qiliang
    Feng, Jun-e
    Wang, Biao
    Meng, Min
    [J]. ASIAN JOURNAL OF CONTROL, 2019, 21 (06) : 2559 - 2568
  • [4] Fault detection problems for Boolean networks and Boolean control networks
    Ettore, Fornasini
    Elena, Valcher Maria
    [J]. 2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, : 1 - 8
  • [5] ON THE OPTIMAL CONTROL OF BOOLEAN CONTROL NETWORKS
    Zhu, Qunxi
    Liu, Yang
    Lu, Jianquan
    Cao, Jinde
    [J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2018, 56 (02) : 1321 - 1341
  • [6] Optimal Control of Boolean Control Networks
    Fornasini, Ettore
    Valcher, Maria Elena
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (05) : 1258 - 1270
  • [7] Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks
    Taou, Nadia S.
    Corne, David W.
    Lones, Michael A.
    [J]. APPLICATIONS OF EVOLUTIONARY COMPUTATION, EVOAPPLICATIONS 2016, PT I, 2016, 9597 : 351 - 362
  • [8] ON IDENTIFICATION OF BOOLEAN CONTROL NETWORKS
    Wang, Biao
    Feng, Jun-e
    Cheng, Daizhan
    [J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2022, 60 (03) : 1591 - 1612
  • [9] On the Full Control of Boolean Networks
    Paul, Soumya
    Pang, Jun
    Su, Cui
    [J]. COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY (CMSB 2018), 2018, 11095 : 313 - 317
  • [10] On detectability of Boolean control networks
    Wang, Biao
    Feng, Jun-e
    Li, Haitao
    Yu, Yongyuan
    [J]. NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2020, 36