文献类型：期刊文献

英文题名：Set Stabilization of Probabilistic Boolean Networks Using Pinning Control

作者：Li, Fangfei[1,2];Xie, Lihua[1]

机构：[1]Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore;[2]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China

年份：2019

卷号：30

期号：8

起止页码：2555

外文期刊名：IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

收录：;EI(收录号：20185006242034);WOS:【SCI-EXPANDED(收录号:WOS:000476787300026)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61773161 and Grant 61673176, in part by the Science and Technology Commission of Shanghai Municipality under Grant 18ZR1409800, in part by the Republic of Singapore National Research Foundation under Grant NRF-CRP8-2011-03, and in part by the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017. (Corresponding author: Fangfei Li.)

语种：英文

外文关键词：Pinning control; probabilistic Boolean network (PBN); semitensor product (STP) of matrices; set stabilization

摘要：Probabilistic Boolean network (PBN) is a kind of stochastic logical system in which update functions are randomly selected from a set of candidate Boolean functions according to a prescribed probability distribution at each time step. In this brief, a pinning controller design algorithm is proposed to set stabilize any PBN with probability one. First, an algorithm is given to change the columns of its transition matrix. Then, according to the newly obtained transition matrix, a fraction of nodes can be selected as pinning nodes to inject control inputs to achieve set stabilization. The problem is challenging since the Boolean functions in a PBN are not deterministic but are randomly chosen among several Boolean functions. Furthermore, the structure matrices of the pinning controllers are given by solving some logical matrices equations based on which a pinning controller design algorithm is provided to set stabilize the PBN with probability one. Finally, the theoretical results are validated using several examples.