{"title":"Observer-based dynamic event-triggered second-level MPC for nonlinear time-delay CPSs under joint hybrid attacks","authors":"Hongchao Song , Zhenlei Wang , Xin Wang","doi":"10.1016/j.amc.2025.129391","DOIUrl":null,"url":null,"abstract":"<div><div>This study investigates observer-based dynamic event-triggered (DET) second-level model predictive control (MPC) for a specific class of nonlinear time-delay cyber-physical systems (CPSs) under hybrid attacks on the sensor-controller (S-C) channel and controller-actuator (C-A) channel. A dynamic event-triggered mechanism with adaptive bias components is developed to reduce trigger frequency, uphold system performance, and conserve communication resources. Additionally, the observer gain is determined using the nominal observation model and linear matrix inequalities. A novel model predictive control approach is devised based on the identified model to enhance system performance. Theoretical analysis demonstrates that the proposed method effectively guarantees that the closed-loop system satisfies the input-to-state practical stability criterion. Finally, a numerical simulation case study is presented to validate the effectiveness of the proposed algorithm.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"498 ","pages":"Article 129391"},"PeriodicalIF":3.5000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325001183","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates observer-based dynamic event-triggered (DET) second-level model predictive control (MPC) for a specific class of nonlinear time-delay cyber-physical systems (CPSs) under hybrid attacks on the sensor-controller (S-C) channel and controller-actuator (C-A) channel. A dynamic event-triggered mechanism with adaptive bias components is developed to reduce trigger frequency, uphold system performance, and conserve communication resources. Additionally, the observer gain is determined using the nominal observation model and linear matrix inequalities. A novel model predictive control approach is devised based on the identified model to enhance system performance. Theoretical analysis demonstrates that the proposed method effectively guarantees that the closed-loop system satisfies the input-to-state practical stability criterion. Finally, a numerical simulation case study is presented to validate the effectiveness of the proposed algorithm.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.