IEEE Trans Neural Netw Learn Syst. 2020 Jun;31(6):2129-2139. doi: 10.1109/TNNLS.2019.2928028. Epub 2019 Aug 9.
In this paper, the output feedback set stabilization problem for Boolean control networks (BCNs) is investigated with the help of the semi-tensor product (STP) tool. The concept of output feedback control invariant (OFCI) subset is introduced, and novel methods are developed to obtain the OFCI subsets. Based on the OFCI subsets, a technique, named spanning tree method, is further introduced to calculate all possible output feedback set stabilizers. An example concerning lac operon for the bacterium Escherichia coli is given to illustrate the effectiveness of the proposed method. This technique can also be used to solve the state feedback (set) stabilization problem for BCNs. Compared with the existing results, our method can dramatically reduce the computational cost when designing all possible state feedback stabilizers for BCNs.
本文借助张量积（STP）工具研究布尔控制网络（BCN）的输出反馈集稳定化问题。引入输出反馈控制不变子集（OFCI）的概念，并开发了新的方法来获得 OFCI 子集。基于 OFCI 子集，进一步引入了一种称为生成树方法的技术，以计算所有可能的输出反馈集稳定器。给出了一个关于细菌大肠杆菌 lac 操纵子的例子来说明所提出方法的有效性。该技术也可用于解决 BCN 的状态反馈（集）稳定化问题。与现有结果相比，我们的方法在设计 BCN 的所有可能状态反馈稳定器时可以显著降低计算成本。
