Smith预估器中基于Markov方法的随机性估计在网络控制系统延迟补偿中的性能提升

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ratish Kumar, Rajiv Kumar, M. Nigam
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引用次数: 0

摘要

到21世纪第二个十年,网络控制系统(NCS)领域有了多方面的技术发展。NCS的发展不仅揭示了它在各个领域的重要应用,也揭示了与之相关的各种困难,这些困难阻碍了网络控制系统的运行。网络引起的延迟是引发许多其他问题的问题,如丢包和带宽利用率的短暂性。本文利用Smith预测器和马尔可夫方法之间的协调来抑制网络引起的延迟。用于仿真的Smith预测器控制器的误差估计是通过马尔可夫方法进行的,该方法通过优化控制信号使系统的控制平稳运行。为了实现所提出的方法,作者在Matlab/Simulink软件中对三阶系统进行了仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Accretion in Delay Compensation of Networked Control System Using Markov Approach-Based Randomness Estimation in Smith Predictor
By the second decade of the 21st century, there has been a multi-faceted technological development in the field of networked control system (NCS). This progression in NCS has not only revealed its significant applications in various areas but has also unveiled various difficulties associated with it that hampered the operations of networked control system. Network-induced delays are issues that promote many other issues like packet dropout and brevity in bandwidth utilization. In this research article, network-induced delay has been curtailed by using the harmony between Smith predictor and Markov approach. The error estimation of the Smith predictor controller used for the simulation is carried out through a Markov approach which allows the control of the system to operate smoothly by optimizing the control signal. To implement the proposed method, the authors have simulated a third order system in Matlab/Simulink software.
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来源期刊
International Journal of System Dynamics Applications
International Journal of System Dynamics Applications COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
自引率
38.90%
发文量
26
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