{"title":"基于ADMM的仿射编队控制加速优化拓扑设计","authors":"Yumeng Wang;Qingkai Yang;Fan Xiao;Hao Fang;Jie Chen","doi":"10.1109/TNSE.2025.3552979","DOIUrl":null,"url":null,"abstract":"This paper studies the problem of topology design for activating affine formation control schemes. The affine formation control exhibits its unique feature as it relies on the stress matrix to dynamically maneuver the whole formation by controlling a small number of agents. Network properties of interest for this design problem generally give rise to optimization formulations within the framework of mixed-integer semidefinite programming (MISDP), resulting in computational inefficiency and NP-hardness. Firstly, to avoid introducing binary variables, the optimization of communication cost is modeled as an <inline-formula><tex-math>$l_{1}$</tex-math></inline-formula>-regularized network sparsity problem. In this way, an optimized topology design method accelerated by the alternating direction method of multipliers (ADMM) is proposed to obtain the stress matrix with low communication cost, fast convergence speed and high tolerance to time-delay. Furthermore, addressing scenarios irrespective of whether the minimum eigenvalue of the stress matrix is prescribed, we propose two enhanced ADMM-based algorithms with closed-form solutions. This is achieved through the transformation of semi-definite constraints in the subproblem into equality constraints. Finally, comparative simulations demonstrate the accelerated effects of the proposed scheme, showcasing its effectiveness in interaction topology construction and optimization for large-scale networks.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2694-2707"},"PeriodicalIF":6.7000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accelerated Optimized Topology Design in Affine Formation Control Using ADMM\",\"authors\":\"Yumeng Wang;Qingkai Yang;Fan Xiao;Hao Fang;Jie Chen\",\"doi\":\"10.1109/TNSE.2025.3552979\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the problem of topology design for activating affine formation control schemes. The affine formation control exhibits its unique feature as it relies on the stress matrix to dynamically maneuver the whole formation by controlling a small number of agents. Network properties of interest for this design problem generally give rise to optimization formulations within the framework of mixed-integer semidefinite programming (MISDP), resulting in computational inefficiency and NP-hardness. Firstly, to avoid introducing binary variables, the optimization of communication cost is modeled as an <inline-formula><tex-math>$l_{1}$</tex-math></inline-formula>-regularized network sparsity problem. In this way, an optimized topology design method accelerated by the alternating direction method of multipliers (ADMM) is proposed to obtain the stress matrix with low communication cost, fast convergence speed and high tolerance to time-delay. Furthermore, addressing scenarios irrespective of whether the minimum eigenvalue of the stress matrix is prescribed, we propose two enhanced ADMM-based algorithms with closed-form solutions. This is achieved through the transformation of semi-definite constraints in the subproblem into equality constraints. Finally, comparative simulations demonstrate the accelerated effects of the proposed scheme, showcasing its effectiveness in interaction topology construction and optimization for large-scale networks.\",\"PeriodicalId\":54229,\"journal\":{\"name\":\"IEEE Transactions on Network Science and Engineering\",\"volume\":\"12 4\",\"pages\":\"2694-2707\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Network Science and Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10933530/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10933530/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Accelerated Optimized Topology Design in Affine Formation Control Using ADMM
This paper studies the problem of topology design for activating affine formation control schemes. The affine formation control exhibits its unique feature as it relies on the stress matrix to dynamically maneuver the whole formation by controlling a small number of agents. Network properties of interest for this design problem generally give rise to optimization formulations within the framework of mixed-integer semidefinite programming (MISDP), resulting in computational inefficiency and NP-hardness. Firstly, to avoid introducing binary variables, the optimization of communication cost is modeled as an $l_{1}$-regularized network sparsity problem. In this way, an optimized topology design method accelerated by the alternating direction method of multipliers (ADMM) is proposed to obtain the stress matrix with low communication cost, fast convergence speed and high tolerance to time-delay. Furthermore, addressing scenarios irrespective of whether the minimum eigenvalue of the stress matrix is prescribed, we propose two enhanced ADMM-based algorithms with closed-form solutions. This is achieved through the transformation of semi-definite constraints in the subproblem into equality constraints. Finally, comparative simulations demonstrate the accelerated effects of the proposed scheme, showcasing its effectiveness in interaction topology construction and optimization for large-scale networks.
期刊介绍:
The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.