摘要
针对分布式预测控制机制下的多智能体系统,该文提出了基于智能体子系统优先级分配的控制策略。利用图论方法对优先级的分配进行描述,并根据最小化系统性能指标确定最佳的优先级分配策略,从而简化分布式预测控制优化问题。对基于优先级的分布式预测控制算法进行了可行性和稳定性分析。仿真结果表明,该文所提出的基于优先级的分布式预测控制方法在获得良好性能的基础上,能够有效地减少子系统之间信息交互的次数,并能够有效降低网络资源利用率。
Aiming at the multi⁃agent system under the distributed predictive control mechanism,this paper proposes a control strategy based on the priority allocation of agent subsystems.The graph theory is used to describe the priority allocation,and the optimal priority allocation strategy is determined according to the minimum system performance index,thus simplifying the distributed predictive control optimization problem.The feasibility and stability of distributed predictive control algorithm based on priority are analyzed.The simulation results show that the priority based distributed predictive control method proposed in this paper can effectively reduce the number of information interactions between subsystems and the utilization of network resources on the basis of good performance.
作者
任凯龙
薛斌强
REN Kailong;XUE Binqiang(College of Automation,Qingdao University,Qingdao 266071,China)
出处
《电子设计工程》
2024年第1期82-85,90,共5页
Electronic Design Engineering
关键词
多智能体系统
优先级
模型预测控制
分布式控制
multi⁃agent system
priority
model predictive control
distributed control
作者简介
任凯龙(1997—),男,湖南岳阳人,硕士研究生。研究方向:分布式模型预测控制。
