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作 者:Henglai Wei Hui Zhang Kamal AI-Haddad Yang Shi
机构地区:[1]Department of Mechanical Engineering,University of Victoria,Victoria,BC V8W 3P6,Canada [2]School of Transportation Science and Engineering,Beihang University,Beijing 100191,China [3]École de Technologie Supérieure,University of Quebec,Montreal,QC H3C 1K3,Canada
出 处:《Engineering》2024年第2期35-46,共12页工程(英文)
基 金:the financial support from the Natural Sciences and Engineering Research Council of Canada(NSERC)。
摘 要:This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.
关 键 词:Model predictive control Resilient control Platoon control Intelligent and connected vehicle Byzantine attacks
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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