Weight Estimation and Secure Control for Discrete Stochastic Distribution Control Systems Under Sparse Sensor Attacks

In this paper, we investigate the problem of weight estimation and secure control for discrete stochastic distribution control (SDC) systems under sparse sensor attacks. Firstly, a Luenberger observer is designed for the linear SDC systems to perform the weight estimation under sparse sensor attacks...

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Bibliographic Details
Published inInternational journal of control, automation, and systems Vol. 21; no. 4; pp. 1119 - 1126
Main Authors Yi, Xiaoyun, Ren, Yuwei, Fang, Yixian, Qi, Li, Niu, Ben
Format Journal Article
LanguageEnglish
Published Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.04.2023
Springer Nature B.V
Subjects
Closed loops
Control
Control systems design
Engineering
Feedback control
Mechatronics
Probability density functions
Proportional integral
Regular Paper
Robotics
Tracking control
Tracking problem
Output probability density functions
stochastic distribution control systems
sparse sensor attacks
weight estimation
proportional-integral controller
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Summary:In this paper, we investigate the problem of weight estimation and secure control for discrete stochastic distribution control (SDC) systems under sparse sensor attacks. Firstly, a Luenberger observer is designed for the linear SDC systems to perform the weight estimation under sparse sensor attacks. Then, a generalized proportional-integral (PI) tracking control strategy is proposed for the linear B-spline model. Furthermore, the tracking problem for output probability density functions (PDFs) is implemented, and the designed controller ensures that the closed-loop system is stable. Finally, the simulation results show the effectiveness of the proposed method.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-021-0868-4