FSG-based divinable time-varying formation tracking of multiple Lagrangian agents with unknown disturbances and directed graphs.

Ding, Teng-Fei; Ge, Ming-Feng; Xiong, Caihua; Liu, Zhi-Wei; Ling, Guang

Ding, Teng-Fei; Ge, Ming-Feng; Xiong, Caihua; Liu, Zhi-Wei; Ling, Guang.

Affiliation

Ding TF; School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430074, China. Electronic address: dingtf@cug.ed
Ge MF; School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China. Electronic address: gemf@cug.edu.cn.
Xiong C; State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: chxiong@hust.edu.cn.
Liu ZW; School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: zwliu@hust.edu.cn.
Ling G; School of Science, Wuhan University of Technology, Wuhan 430070, China. Electronic address: guangling@whut.edu.cn.

ISA Trans ; 132: 278-291, 2023 Jan.

Article de En | MEDLINE | ID: mdl-35760655

Mots clés

Directed graphs; Divinable time-varying formation tracking (TVFT); Flexible shape generator (FSG); Multiple Lagrangian agents; Unknown disturbances

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies Langue: En Journal: ISA Trans Année: 2023 Type de document: Article Pays de publication: États-Unis d'Amérique

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