文献类型：期刊文献

英文题名：A Proportional-Integral-Derivative Inspired Model for Opinion Dynamics in a Trust Relationship Network

作者：Ji, Chunli[1];Dai, Yuehua[2];Lu, Xiwen[3];Zhang, Wenjun[4]

机构：[1]Shanghai Univ Polit Sci & Law, Sch Econ & Management, Shanghai 201701, Peoples R China;[2]Shanghai Dev Strategy Res Inst, Dept Stat, Shanghai 200032, Peoples R China;[3]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China;[4]Univ Saskatchewan, Dept Mech Engn, Saskatoon, SK S7N 5A9, Canada

年份：2024

卷号：54

期号：5

起止页码：3056

外文期刊名：IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

收录：;EI(收录号：20240815581511);WOS:【SCI-EXPANDED(收录号:WOS:001164154200001)】；

基金：No Statement Available

语种：英文

外文关键词：Numerical models; Biological system modeling; Decision making; Context modeling; Convergence; PD control; Mathematical models; Consensus; opinion dynamics (OD); proportional-integral-derivative (PID); trust relationship network

摘要：Opinion dynamics (OD) studies the members' opinion formation process to a specific issue in a group interacting environment. The existing literature seldom considers the implicit information of their opinions and neighboring members' influence during iterations. This article first proposes a method to describe the members' mental processes of changing opinions based on the support information that consists of the trust relationship among the neighboring members and the difference among the neighboring members' opinions, and this method is named the support-based method. Then, a convergence condition based on the network structure is given, and an analysis of the convergence of the model is also provided. Further, inspired by the idea of the proportional-integral-derivative (PID) controller, we propose a new method to capture the opinion changes in three areas: 1) the past cumulative performance; 2) the current performance; and 3) the future trend of the performance, and this method is named PID-inspired method. Numerical experiments are provided to validate the effectiveness of the support-based method and the PID-inspired method; specifically, the PID-inspired method has a higher-convergence rate than the support-based method.