具有用户数据报协议流的多传输控制协议/主动队列管理网络的指令过滤式后退控制

IF 2.7 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Asian Journal of Control Pub Date : 2024-06-05 DOI:10.1002/asjc.3417

Lei Nie, Meng Wang, Huaicheng Yan, Zhichen Li, Yongxiao Tian

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引用次数: 0

摘要

本研究探讨了具有用户数据报协议（UDP）流的多传输控制协议/主动队列管理（TCP/AQM）网络的拥塞控制问题。将 UDP 流作为未知干扰，通过最小最大定理求得最大干扰。通过后退控制和指令滤波技术，为多 TCP/AQM 网络设计了一种新型控制算法。通过仿真研究验证了所提方法的有效性和可行性。

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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Command filtered backstepping control of multiple transmission control protocol/active queue management networks with user datagram protocol flows

In this study, the congestion control problem for multiple transmission control protocol/active queue management (TCP/AQM) networks with user datagram protocol (UDP) flows is investigated. Taking the UDP stream as the unknown interference and the maximum interference is obtained by the minimax theorem. A novel control algorithm is designed for multi-TCP/AQM networks through backstepping control and command filtered technology. Simulation studies are carried out to verify the effectiveness and feasibility of the proposed method.

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来源期刊

Asian Journal of Control 工程技术-自动化与控制系统

CiteScore

4.80

自引率

25.00%

发文量

253

审稿时长

7.2 months

期刊介绍： The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application. Published six times a year, the Journal aims to be a key platform for control communities throughout the world. The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive. Topics include: The theory and design of control systems and components, encompassing: Robust and distributed control using geometric, optimal, stochastic and nonlinear methods Game theory and state estimation Adaptive control, including neural networks, learning, parameter estimation and system fault detection Artificial intelligence, fuzzy and expert systems Hierarchical and man-machine systems All parts of systems engineering which consider the reliability of components and systems Emerging application areas, such as: Robotics Mechatronics Computers for computer-aided design, manufacturing, and control of various industrial processes Space vehicles and aircraft, ships, and traffic Biomedical systems National economies Power systems Agriculture Natural resources.