Quantized iterative learning control for nonlinear multi-agent systems with initial state error

Zhang, Ting; Li, Ning; Chen, Jiaxi

doi:10.1016/j.sysconle.2024.105756

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2024

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“…Iterative learning control (ILC) technology is particularly suitable for addressing consensus problems in multi-agent systems [4,5]. ILC excels in formation control for MASs, especially in repetitive tasks over finite time intervals.…”

Section: Introductionmentioning

confidence: 99%

Iterative Learning Formation Control via Input Sharing for Fractional-Order Singular Multi-Agent Systems with Local Lipschitz Nonlinearity

Wang,

et al. 2024

Fractal Fract

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For a class of fractional-order singular multi-agent systems (FOSMASs) with local Lipschitz nonlinearity, this paper proposes a closed-loop Dα-type iterative learning formation control law via input sharing to achieve the stable formation of FOSMASs in a finite time. Firstly, the formation control issue of FOSMASs with local Lipschitz nonlinearity under the fixed communication topology (FCT) is transformed into the consensus tracking control scenario. Secondly, by virtue of utilizing the characteristics of fractional calculus and the generalized Gronwall inequality, sufficient conditions for the convergence of formation error are given. Then, drawing upon the FCT, the iteration-varying switching communication topology is considered and examined. Ultimately, the validity of the Dα-type learning method is showcased through two numerical cases.

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Section: Introductionmentioning

confidence: 99%