Adaptive fuzzy formation control for heterogeneous multi-agent systems using time-varying IBLFs

Hou, Han‐Qian; Liu, Lei; Lan, Jie

doi:10.1007/s11071-023-08686-2

Cited by 5 publications

(1 citation statement)

References 48 publications

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“…In recent times, owing to escalating societal demands, there has been a significant advancement in the development of unmanned systems [1][2][3]. These systems offer benefits such as compactness, agility, affordability, and the elimination of casualty risks [4][5][6]. They can operate in hazardous zones or areas unsuitable for manned vehicles, broaden operational possibilities, and are cost effective [7,8].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Distributed Heterogeneous Formation Control for UAV-USVs with Input Quantization

Ning,

Huang,

Liu

et al. 2024

JMSE

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This paper investigates the cooperative formation trajectory tracking problem for heterogeneous unmanned aerial vehicle (UAV) and multiple unmanned surface vessel (USV) systems with input quantization performance. Firstly, at the kinematic level, a distributed guidance law based on an extended state observer (ESO) is designed to compensate for the unknown speed of neighbor agents for expected trajectory tracking, and subsequently at the dynamic level, an ESO is utilized to estimate model uncertainties and environmental disturbances. Following that, a linear analytic model is employed to depict the input quantization process, and the corresponding adaptive quantization controller is designed without necessitating prior information on quantization parameters. Based on the input-to-state stability, the stability of the proposed control structure is proved, and all the signals in the closed-loop system are ultimately bounded. Finally, a simulation study is provided to show the efficacy of the proposed strategy.

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