Optimal control input for discrete-time networked control systems with data dropout

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Tadanao Zanma, Naohiro Yamamoto, Kenta Koiwa, Kang-Zhi Liu
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引用次数: 1

Abstract

These days, networked control systems (NCSs) in which data is transmitted via communication have been actively studied for many potential applications. In an NCS, data dropout degrades control performance depending on network conditions. For an NCS with data dropout, the authors propose a model-predictive-control-based input optimisation, representing data dropout as both a Bernoulli model and a finite-order Markov chain. Using the proposed NCS data dropout model, the authors derive an optimal input that provides the estimated error between the expected state of the plant and a given reference. The proposed control problem is formulated as its equivalent quadratic programming, as executed at each online sampling. The authors also demonstrate simulations and experiments to show the effectiveness of the proposed method.

Abstract Image

具有数据丢失的离散网络控制系统的最优控制输入
如今,通过通信传输数据的网络控制系统(NCSs)已被积极研究用于许多潜在的应用。在NCS中,根据网络条件的不同,数据丢失会降低控制性能。对于具有数据丢失的NCS,作者提出了一种基于模型预测控制的输入优化,将数据丢失表示为伯努利模型和有限阶马尔可夫链。利用提出的NCS数据丢失模型,作者得出了一个最优输入,该输入提供了工厂预期状态与给定参考之间的估计误差。所提出的控制问题被表述为在每次在线采样时执行的等效二次规划。通过仿真和实验验证了该方法的有效性。
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来源期刊
IET Cyber-Physical Systems: Theory and Applications
IET Cyber-Physical Systems: Theory and Applications Computer Science-Computer Networks and Communications
CiteScore
5.40
自引率
6.70%
发文量
17
审稿时长
19 weeks
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