On Optimal Time-Varying Feedback Controllability for Probabilistic Boolean Control Networks

被引：30
作者：
Toyoda, Mitsuru [1 ]
Wu, Yuhu [2 ,3 ]
机构：
[1] Inst Stat Math, Tokyo 1068569, Japan
[2] Dalian Univ Technol, Key Lab Intelligent Control & Optimizat Ind Equip, Minist Educ, Dalian 116024, Peoples R China
[3] Dalia Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2020年 / 31卷 / 06期
基金：
日本学术振兴会; 中国国家自然科学基金;
关键词：
Controllability; Probabilistic logic; Optimal control; Boolean functions; Optimization; State feedback; Adaptive control; probabilistic Boolean control network (PBCN); semitensor product (STP); stochastic optimal control; DYNAMICS; SYNCHRONIZATION; OBSERVABILITY; DESIGN; STABILIZATION; EXPRESSION; ALGORITHM;
D O I：
10.1109/TNNLS.2019.2927241
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This brief studies controllability for probabilistic Boolean control network (PBCN) with time-varying feedback control laws. The concept of feedback controllability with an arbitrary probability for PBCNs is formulated first, and a control problem to maximize the probability of time-varying feedback controllability is investigated afterward. By introducing semitensor product (STP) technique, an equivalent multistage decision problem is deduced, and then a novel optimization algorithm is proposed to obtain the maximum probability of controllability and the corresponding optimal feedback law simultaneously. The advantages of the time-varying optimal controller obtained by the proposed algorithm, compared to the time-invariant one, are illustrated by numerical simulations.
引用
收藏
页码：2202 / 2208
页数：7
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