{"title":"Adaptive Dynamic Formation Control of Robotic Vehicle Systems Based on Rigid Graph Theory","authors":"Guanglei Zhao, Lu Luo, Changchun Hua","doi":"10.1007/s12555-023-0189-x","DOIUrl":null,"url":null,"abstract":"<p>In this paper, dynamic formation problem of three-dimensional (3D) robotic vehicle systems with nonholonomic constraint and dynamics model is investigated. The control objectives are to achieve formation acquisition (i.e., vehicles form a predefined geometric shape) and formation maneuvering (vehicles move as a whole following predefined velocity). For the first objective, the nonlinear model is transformed into a dynamic model similar as the Euler-Lagrangian system with uncertain parameters. Then, we propose a rigid graph based adaptive dynamic formation control law, which enables the robotic vehicle system to converge to the target formation. Meanwhile, collision avoidance between vehicles can be achieved because the rigid graph theory naturally ensures the distance constraint. Then, formation maneuvering problem is investigated, on the basis of formation acquisition, a predefined velocity signal is added to the proposed adaptive formation control law such that robotic vehicles move as a whole following the predefined velocity. Compared with the existing results, the proposed rigid graph based formation control method can effectively reduce the appearance of non-desired equilibrium points of traditional distance based methods, moreover, the distance between robot vehicles can be time-varying, and the formation shape or size can be time-varying. Simulation results confirm the effectiveness of the dynamic formation control law.</p>","PeriodicalId":54965,"journal":{"name":"International Journal of Control Automation and Systems","volume":"20 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Control Automation and Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12555-023-0189-x","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}
引用次数: 0
Abstract
In this paper, dynamic formation problem of three-dimensional (3D) robotic vehicle systems with nonholonomic constraint and dynamics model is investigated. The control objectives are to achieve formation acquisition (i.e., vehicles form a predefined geometric shape) and formation maneuvering (vehicles move as a whole following predefined velocity). For the first objective, the nonlinear model is transformed into a dynamic model similar as the Euler-Lagrangian system with uncertain parameters. Then, we propose a rigid graph based adaptive dynamic formation control law, which enables the robotic vehicle system to converge to the target formation. Meanwhile, collision avoidance between vehicles can be achieved because the rigid graph theory naturally ensures the distance constraint. Then, formation maneuvering problem is investigated, on the basis of formation acquisition, a predefined velocity signal is added to the proposed adaptive formation control law such that robotic vehicles move as a whole following the predefined velocity. Compared with the existing results, the proposed rigid graph based formation control method can effectively reduce the appearance of non-desired equilibrium points of traditional distance based methods, moreover, the distance between robot vehicles can be time-varying, and the formation shape or size can be time-varying. Simulation results confirm the effectiveness of the dynamic formation control law.
期刊介绍:
International Journal of Control, Automation and Systems is a joint publication of the Institute of Control, Robotics and Systems (ICROS) and the Korean Institute of Electrical Engineers (KIEE).
The journal covers three closly-related research areas including control, automation, and systems.
The technical areas include
Control Theory
Control Applications
Robotics and Automation
Intelligent and Information Systems
The Journal addresses research areas focused on control, automation, and systems in electrical, mechanical, aerospace, chemical, and industrial engineering in order to create a strong synergy effect throughout the interdisciplinary research areas.