Generalized cyclic pursuit: An estimator-based model-reference adaptive control approach

Antoine Ansart, Jyh Ching Juang

研究成果: Conference contribution

摘要

The paper proposes an estimation and control method about sustaining the motion of a group of autonomous agents under the Generalized Cyclic Pursuit (GCP) laws, where formation patterns can be formed by assigning eigenvalues of the system to be marginally stable. In the present paper, a Linear Quadratic Estimator (LQE), used to estimate the absolute position based on information exchange, is coupled with a Model Reference Adaptive Control (MRAC) to sustain the motion of agents and thus maintain the desired patterns in the presence of uncertainties and noise. Simulation results are provided to verify the proposed approach in area coverage applications.

原文English
主出版物標題2020 28th Mediterranean Conference on Control and Automation, MED 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面598-604
頁數7
ISBN(電子)9781728157429
DOIs
出版狀態Published - 2020 九月
事件28th Mediterranean Conference on Control and Automation, MED 2020 - Saint-Raphael, France
持續時間: 2020 九月 152020 九月 18

出版系列

名字2020 28th Mediterranean Conference on Control and Automation, MED 2020

Conference

Conference28th Mediterranean Conference on Control and Automation, MED 2020
國家France
城市Saint-Raphael
期間20-09-1520-09-18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Control and Optimization
  • Modelling and Simulation

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