Scholarlink

<p>For fully actuated multi-agent systems (FAMASs), this paper presents a fault-tolerant formation control strategy grounded in a distributed predictive control framework. With the aid of the state information of neighbouring agents, a discrete distributed fault estimation observer is devised to accurately estimate actuator faults within the FAMASs. Subsequently, leveraging the high-order fully actuated characteristics of FAMAS and the obtained fault estimation information, a fully actuated system approach is employed to construct a fault-tolerant formation controller, which can mitigate the adverse impacts caused by actuator faults and the nonlinear dynamics. Furthermore, the designed controller incorporates a predictive control element, derived by minimizing a cost function related to the multi-step-ahead prediction of formation errors and control inputs. This approach ensures the stability of the FAMAS formation while optimizing control performance. Finally, the effectiveness of the proposed method is proven through its application to UAV formation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Predictive Control Strategy Based Fault-Tolerant Formation Control for Fully Actuated Multi-Agent Systems

  • 期刊论文

  • 发表日期：

    2025年5月1日

查看全文
  • Yuan Lu,
  • Jingping Xia,
  • Lihua Shen,
  • Ke Zhang

摘要

For fully actuated multi-agent systems (FAMASs), this paper presents a fault-tolerant formation control strategy grounded in a distributed predictive control framework. With the aid of the state information of neighbouring agents, a discrete distributed fault estimation observer is devised to accurately estimate actuator faults within the FAMASs. Subsequently, leveraging the high-order fully actuated characteristics of FAMAS and the obtained fault estimation information, a fully actuated system approach is employed to construct a fault-tolerant formation controller, which can mitigate the adverse impacts caused by actuator faults and the nonlinear dynamics. Furthermore, the designed controller incorporates a predictive control element, derived by minimizing a cost function related to the multi-step-ahead prediction of formation errors and control inputs. This approach ensures the stability of the FAMAS formation while optimizing control performance. Finally, the effectiveness of the proposed method is proven through its application to UAV formation.