Optimal control for networked control system with Markovian packet loss and delay

IF 2.7 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Asian Journal of Control Pub Date : 2024-04-28 DOI:10.1002/asjc.3395
Hongxia Wang, Tao Liu, Zixing Li, Xiao Liang
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Abstract

This paper focuses on the optimal output-feedback control and stabilization of a networked control system, where both time delay and packet loss are involved. Different from most previous work, the packet loss is Markovian, and the time delay occurs between the actuator and controller. The difficulty is rooted in the failure of the separation principle. The main tools are solving the delayed forward-backward stochastic difference equations (D-FBSDEs) and convergent analysis. Resorting to solving D-FBSDEs and completing the square, we acquire the analytical solution, including the necessary and sufficient solvability condition and the explicit controller, of the finite-horizon optimal control problem. Based on the finite-horizon result and convergent analysis, we then obtain the analytical solution of the infinite-horizon optimal control and stabilization problems. In addition, by analyzing the convergence of the optimal estimator, we establish a constraint relationship between the packet loss probability q $$ q $$ and the system matrix A $$ A $$ . The results are evaluated by numerical examples.

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具有马尔可夫丢包和延迟的网络控制系统的最优控制
本文重点研究网络控制系统的最优输出反馈控制和稳定问题,其中涉及时间延迟和数据包丢失。与以往大多数研究不同的是,数据包丢失是马尔可夫式的,而时间延迟发生在执行器和控制器之间。困难的根源在于分离原理的失效。主要工具是求解延迟前向后向随机差分方程(D-FBSDE)和收敛分析。通过求解 D-FBSDE 和补全平方,我们获得了有限视距最优控制问题的解析解,包括必要和充分可解条件以及显式控制器。在有限视距结果和收敛分析的基础上,我们又得到了无限视距最优控制和稳定问题的解析解。此外,通过分析最优估计器的收敛性,我们建立了丢包概率 q$$ q $$ 和系统矩阵 A$$ A $$ 之间的约束关系。我们通过数值示例对结果进行了评估。
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来源期刊
Asian Journal of Control
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.
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