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Generalized Cyclic Pursuit: A Model-Reference Adaptive Control Approach

研究成果: Conference contribution

9   連結會在新分頁中開啟 引文 斯高帕斯(Scopus)

摘要

The paper proposes a method about sustaining the motion of a group of autonomous agents under the Generalized Cyclic Pursuit (GCP) laws. Under GCP, formation patterns can be formed by assigning eigenvalues of the system to be marginally stable. Such a control, however, is sensitive to parameter variation. In the paper, Model Reference Adaptive Control (MRAC) technique is employed to sustain the motion of agents and thus maintain the desired patterns in the presence of uncertainties. Simulation results are provided to verify the proposed approach.

原文English
主出版物標題2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面89-94
頁數6
ISBN(電子)9781728167916
DOIs
出版狀態Published - 2020 4月
事件5th International Conference on Control and Robotics Engineering, ICCRE 2020 - Osaka, Japan
持續時間: 2020 4月 242020 4月 26

出版系列

名字2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020

Conference

Conference5th International Conference on Control and Robotics Engineering, ICCRE 2020
國家/地區Japan
城市Osaka
期間20-04-2420-04-26

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 機械工業
  • 控制和優化

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