@inproceedings{465a6c25c2d943ffb92603b355b300f6,
title = "A Full-Form Dynamic Linearization Data Model-Based Model-Free Adaptive Formation Control Method for Nonlinear Multi-agents",
abstract = "This paper addresses the model-free adaptive formation control (MFAFC) problem of the nonlinear multiagent system. First, the standardized formation tracking error is designed to fit the controller design framework of the model-free adaptive control. Then, the update law of the pseudo-gradient (PG) vectors is designed. In addition, the full-form dynamic linearization(FFDL) data model-based model-free adaptive formation controller is given to eliminate the designed standardized formation tracking error. Finally, the boundedness of the tracking error is proved theoretically, and a simulation example is given to prove the effectiveness.",
keywords = "Formation control, Model-free adaptive control, Nonlinear multiagent system",
author = "Tian Chen and Yifei Zhang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023 ; Conference date: 24-11-2023 Through 27-11-2023",
year = "2024",
doi = "10.1007/978-981-97-3340-8\_28",
language = "英语",
isbn = "9789819733392",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "309--316",
editor = "Guo-Ping Jiang and Mengyi Wang and Zhang Ren",
booktitle = "Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Guidance Technologies",
address = "德国",
}