Weilun Zhang , Guan Wang , Hongwei Xia , Guangcheng Ma
{"title":"具有预定性能和避碰的空气轴承机器人编队的层次混合事件触发神经控制","authors":"Weilun Zhang , Guan Wang , Hongwei Xia , Guangcheng Ma","doi":"10.1016/j.actaastro.2025.09.007","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes a hierarchical adaptive control architecture with flexible prescribed performance for consensus tracking in air bearing robots (ABR) formations under constrained communications and external disturbances. A hierarchical control framework is proposed, which interconnects leaders and followers through a virtual system, preventing collisions among air-bearing robots through upper-layer prescribed performance parameter design while blocking mutual propagation of disturbance or fault signals. To address unmeasurable velocity and unknown disturbances, a novel neural network based extended state observer is synthesized, which using one algebraic iteration as the iterative learning algorithm to reduce computational complexity. Furthermore, a saturation threshold hybrid triggering strategy with transient performance guarantees is proposed, effectively reducing communication overhead by 48% while preventing actuator saturation-induced fragility in multi-constraint scenarios. Theoretical analysis guarantees system stability, and experimental results demonstrate the method’s effectiveness.</div></div>","PeriodicalId":44971,"journal":{"name":"Acta Astronautica","volume":"238 ","pages":"Pages 443-459"},"PeriodicalIF":3.4000,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hierarchical hybrid event-triggered neural control for air-bearing robot formation with prescribed performance and collision avoidance\",\"authors\":\"Weilun Zhang , Guan Wang , Hongwei Xia , Guangcheng Ma\",\"doi\":\"10.1016/j.actaastro.2025.09.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper proposes a hierarchical adaptive control architecture with flexible prescribed performance for consensus tracking in air bearing robots (ABR) formations under constrained communications and external disturbances. A hierarchical control framework is proposed, which interconnects leaders and followers through a virtual system, preventing collisions among air-bearing robots through upper-layer prescribed performance parameter design while blocking mutual propagation of disturbance or fault signals. To address unmeasurable velocity and unknown disturbances, a novel neural network based extended state observer is synthesized, which using one algebraic iteration as the iterative learning algorithm to reduce computational complexity. Furthermore, a saturation threshold hybrid triggering strategy with transient performance guarantees is proposed, effectively reducing communication overhead by 48% while preventing actuator saturation-induced fragility in multi-constraint scenarios. Theoretical analysis guarantees system stability, and experimental results demonstrate the method’s effectiveness.</div></div>\",\"PeriodicalId\":44971,\"journal\":{\"name\":\"Acta Astronautica\",\"volume\":\"238 \",\"pages\":\"Pages 443-459\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Astronautica\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0094576525005776\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Astronautica","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0094576525005776","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
Hierarchical hybrid event-triggered neural control for air-bearing robot formation with prescribed performance and collision avoidance
This paper proposes a hierarchical adaptive control architecture with flexible prescribed performance for consensus tracking in air bearing robots (ABR) formations under constrained communications and external disturbances. A hierarchical control framework is proposed, which interconnects leaders and followers through a virtual system, preventing collisions among air-bearing robots through upper-layer prescribed performance parameter design while blocking mutual propagation of disturbance or fault signals. To address unmeasurable velocity and unknown disturbances, a novel neural network based extended state observer is synthesized, which using one algebraic iteration as the iterative learning algorithm to reduce computational complexity. Furthermore, a saturation threshold hybrid triggering strategy with transient performance guarantees is proposed, effectively reducing communication overhead by 48% while preventing actuator saturation-induced fragility in multi-constraint scenarios. Theoretical analysis guarantees system stability, and experimental results demonstrate the method’s effectiveness.
期刊介绍:
Acta Astronautica is sponsored by the International Academy of Astronautics. Content is based on original contributions in all fields of basic, engineering, life and social space sciences and of space technology related to:
The peaceful scientific exploration of space,
Its exploitation for human welfare and progress,
Conception, design, development and operation of space-borne and Earth-based systems,
In addition to regular issues, the journal publishes selected proceedings of the annual International Astronautical Congress (IAC), transactions of the IAA and special issues on topics of current interest, such as microgravity, space station technology, geostationary orbits, and space economics. Other subject areas include satellite technology, space transportation and communications, space energy, power and propulsion, astrodynamics, extraterrestrial intelligence and Earth observations.