Finite-time adaptive neural command filtered control for non-strict feedback uncertain multi-agent systems including prescribed performance and input nonlinearities
作者：
Highlights：
• highlights
• Finite-time consensus tracking control is proposed for uncertain nonlinear multi-agent systems with prescribed performance and input saturation.
• By constructing a finite-time performance function, the tracking errors converge to a predefined attenuation range within finite-time.
• The unmodeled dynamics and dynamic disturbances of the system are handled by means of measurable dynamic signals.
• The coupling problem between multi-agents and the system controller design problem in non-strict feedback form are successfully dealt with.
• A finite-time adaptive neural controller is designed based on command filter.
摘要
highlights•Finite-time consensus tracking control is proposed for uncertain nonlinear multi-agent systems with prescribed performance and input saturation.•By constructing a finite-time performance function, the tracking errors converge to a predefined attenuation range within finite-time.•The unmodeled dynamics and dynamic disturbances of the system are handled by means of measurable dynamic signals.•The coupling problem between multi-agents and the system controller design problem in non-strict feedback form are successfully dealt with.•A finite-time adaptive neural controller is designed based on command filter.
论文关键词：Multi-agent systems,Prescribed performance,Input nonlinearities,Finite-time control,Command filter,Unmodeled dynamics
论文评审过程：Received 3 August 2021, Revised 17 December 2021, Accepted 14 January 2022, Available online 31 January 2022, Version of Record 31 January 2022.
论文官网地址：https://doi.org/10.1016/j.amc.2022.126953
