Evacuation by leader-follower model with bounded confidence and predictive mechanisms

IF 1.2 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS Archives of Control Sciences Pub Date : 2023-07-20 DOI:10.24425/acs.2021.138695
R. Almeida, E. Girejko, Luís Machado, A. Malinowska, Natália Martins
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引用次数: 1

Abstract

This paper studies an evacuation problem described by a leader-follower model with bounded confidence under predictive mechanisms. We design a control strategy in such a way that agents are guided by a leader, which follows the evacuation path. The proposed evacuation algorithm is based on Model Predictive Control (MPC) that uses the current and the past information of the system to predict future agents’ behaviors. It can be observed that, with MPC method, the leader-following consensus is obtained faster in comparison to the conventional optimal control technique. The effectiveness of the developed MPC evacuation algorithm with respect to different parameters and different time domains is illustrated by numerical examples.
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具有有限置信度和预测机制的领导-追随者疏散模型
本文研究了在预测机制下由有界置信度的领导-随从模型描述的疏散问题。我们设计了一种控制策略,在这种方式下,代理由领导者引导,领导者遵循疏散路径。该疏散算法基于模型预测控制(MPC),利用系统的当前和过去信息来预测未来智能体的行为。可以看出,与传统的最优控制技术相比,MPC方法可以更快地获得领导-跟随共识。数值算例说明了所提出的MPC疏散算法在不同参数和不同时域下的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Archives of Control Sciences
Archives of Control Sciences Mathematics-Modeling and Simulation
CiteScore
2.40
自引率
33.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.
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