{"title":"H∞ Optimal Distributed Tracking Control Algorithm for Network Distributed Systems with an Application to UAV","authors":"Gulnihal Kucuksayacigil","doi":"10.1109/ICUAS57906.2023.10156349","DOIUrl":null,"url":null,"abstract":"In this work, a recursive algorithm has been developed for heterogeneous network distributed systems (NDS) communicating over an undirected network to solve H∞ optimal distributed tracking control problem of continuous-time systems as a convex problem. Recent studies on NDS have studied the tracking control problem with decentralized performance functions defined for each subsystem in the network, on the contrary, a global performance function has been defined in this work for the whole NDS. An optimal distributed control problem has been defined as a sequential convex optimization problem benefiting off-policy reinforcement learning with sparsity constraints introduced on the symmetric positive definite matrix. Finally, the efficacy of the proposed algorithm is shown on a group of heterogeneous unmanned aerial vehicles (UAV) communicating over an undirected network.","PeriodicalId":379073,"journal":{"name":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS57906.2023.10156349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this work, a recursive algorithm has been developed for heterogeneous network distributed systems (NDS) communicating over an undirected network to solve H∞ optimal distributed tracking control problem of continuous-time systems as a convex problem. Recent studies on NDS have studied the tracking control problem with decentralized performance functions defined for each subsystem in the network, on the contrary, a global performance function has been defined in this work for the whole NDS. An optimal distributed control problem has been defined as a sequential convex optimization problem benefiting off-policy reinforcement learning with sparsity constraints introduced on the symmetric positive definite matrix. Finally, the efficacy of the proposed algorithm is shown on a group of heterogeneous unmanned aerial vehicles (UAV) communicating over an undirected network.