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Leader-following output-feedback consensus for second order multiagent systems with arbitrary convergence time and prescribed performance.
Gong, Wenquan; Li, Bo; Yang, Yongsheng; Xiao, Bing; Ran, Dechao.
Afiliação
  • Gong W; Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, 201306, China. Electronic address: wqgong902@gmail.com.
  • Li B; Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, 201306, China. Electronic address: nemo127@163.com.
  • Yang Y; Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, 201306, China. Electronic address: yangys@shmtu.edu.cn.
  • Xiao B; School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China. Electronic address: xiaobing@nwpu.edu.cn.
  • Ran D; National Innovation Institute of Defense Technology, Chinese Academy of Military Science, Beijing, 100071, China. Electronic address: rdcno.11002@163.com.
ISA Trans ; 141: 251-260, 2023 Oct.
Article em En | MEDLINE | ID: mdl-37495495
ABSTRACT
This paper investigates the prescribed-time leader-following output-feedback consensus problem for second order multiagent systems without velocity measurement. Firstly, by introducing a time-scaling function, novel prescribed-time state observers are designed to estimate the second-order states of the agents. Then, a distributed output-feedback scheme is proposed to achieve leader-following consensus, where the transient performance, including the convergence rate and the overshoot, can be offline pre-assigned. It should be noted that the singularity-like problem is solved for the system under measurement errors by adopting a form of piecewise functions. Moreover, the control strategy is modified by introducing an auxiliary system when taking the common saturation problem into account. Finally, the efficiency of the proposed schemes is illustrated by numerical simulation examples.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article