{"title":"多平流层飞艇在未知非均匀风场中的自适应协同覆盖控制","authors":"","doi":"10.1016/j.jfranklin.2024.107244","DOIUrl":null,"url":null,"abstract":"<div><p>This paper investigates the coverage control problem for Multi-Stratospheric Airship (MSA) system within unknown non-uniform wind field. To address the challenge of deploying airships strategically in regions with weak wind, an adaptive collaborative coverage control algorithm is proposed. The algorithm includes a coverage planning approach based on wind field estimation and an airship motion control approach. Firstly, as accurate wind field data in the mission area is unavailable, an adaptive estimation algorithm based on the Gaussian approximation method is proposed to estimate the wind data. This involves processing discrete wind field sampling information with a density function. Secondly, an event-triggered dynamic tracking controller with a neural network to handle model uncertainties is proposed to steer the MSA system approaching a near-optimal configuration. Additionally, convergence of the coverage system is proven through a Lyapunov-like proof. Simulation results illustrate the superior performance of the adaptive collaborative coverage control algorithm.</p></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive collaborative coverage control for Multi-Stratospheric Airship within unknown non-uniform wind field\",\"authors\":\"\",\"doi\":\"10.1016/j.jfranklin.2024.107244\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper investigates the coverage control problem for Multi-Stratospheric Airship (MSA) system within unknown non-uniform wind field. To address the challenge of deploying airships strategically in regions with weak wind, an adaptive collaborative coverage control algorithm is proposed. The algorithm includes a coverage planning approach based on wind field estimation and an airship motion control approach. Firstly, as accurate wind field data in the mission area is unavailable, an adaptive estimation algorithm based on the Gaussian approximation method is proposed to estimate the wind data. This involves processing discrete wind field sampling information with a density function. Secondly, an event-triggered dynamic tracking controller with a neural network to handle model uncertainties is proposed to steer the MSA system approaching a near-optimal configuration. Additionally, convergence of the coverage system is proven through a Lyapunov-like proof. Simulation results illustrate the superior performance of the adaptive collaborative coverage control algorithm.</p></div>\",\"PeriodicalId\":17283,\"journal\":{\"name\":\"Journal of The Franklin Institute-engineering and Applied Mathematics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of The Franklin Institute-engineering and Applied Mathematics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0016003224006653\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of The Franklin Institute-engineering and Applied Mathematics","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0016003224006653","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Adaptive collaborative coverage control for Multi-Stratospheric Airship within unknown non-uniform wind field
This paper investigates the coverage control problem for Multi-Stratospheric Airship (MSA) system within unknown non-uniform wind field. To address the challenge of deploying airships strategically in regions with weak wind, an adaptive collaborative coverage control algorithm is proposed. The algorithm includes a coverage planning approach based on wind field estimation and an airship motion control approach. Firstly, as accurate wind field data in the mission area is unavailable, an adaptive estimation algorithm based on the Gaussian approximation method is proposed to estimate the wind data. This involves processing discrete wind field sampling information with a density function. Secondly, an event-triggered dynamic tracking controller with a neural network to handle model uncertainties is proposed to steer the MSA system approaching a near-optimal configuration. Additionally, convergence of the coverage system is proven through a Lyapunov-like proof. Simulation results illustrate the superior performance of the adaptive collaborative coverage control algorithm.
期刊介绍:
The Journal of The Franklin Institute has an established reputation for publishing high-quality papers in the field of engineering and applied mathematics. Its current focus is on control systems, complex networks and dynamic systems, signal processing and communications and their applications. All submitted papers are peer-reviewed. The Journal will publish original research papers and research review papers of substance. Papers and special focus issues are judged upon possible lasting value, which has been and continues to be the strength of the Journal of The Franklin Institute.