Neurocomputing, ( ISI ), Volume (397), Year (2020-7) , Pages (212-223)

Title : ( Bipartite consensus control for fractional-order nonlinear multi-agent systems: An output constraint approach )

Authors: Milad Shahvali , ALI AZARBAHRAM , Mohammad Bagher Naghibi Sistani , Javad Askari ,

Citation: BibTeX | EndNote

Abstract

Bipartite consensus of multiple fractional-order nonlinear systems with output constraints is assessed under signed graph. The agents’ model is completely unknown with high-order heterogeneous strict-feedback dynamics and external disturbances, which cover single- and double-integrator integer-order systems as special forms. To ensure the bipartite consensus task, a novel fully distributed controller is developed based on backstepping technique and neuro-adaptive update mechanism. A barrier Lyapunov function is introduced to limit the followers’ outputs within the preset bounds. Algebraic graph theory and Lyapunov fractional-order stability theorem are employed to deal with the analysis difficulties caused by the network of fractional-order dynamics. Sufficient conditions on bipartite consensus is established, and it is also shown that all the closed-loop error signals are uniformly ultimately bounded. The simulation results are carried out to demonstrate the effectiveness of the proposed approach.

Keywords

, Fractional, order systems Multi, agent systems Barrier Lyapunov function Backstepping nonlinear control Consensus
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@article{paperid:1087722,
author = {Shahvali, Milad and AZARBAHRAM, ALI and Naghibi Sistani, Mohammad Bagher and Javad Askari},
title = {Bipartite consensus control for fractional-order nonlinear multi-agent systems: An output constraint approach},
journal = {Neurocomputing},
year = {2020},
volume = {397},
month = {July},
issn = {0925-2312},
pages = {212--223},
numpages = {11},
keywords = {Fractional-order systems Multi-agent systems Barrier Lyapunov function Backstepping nonlinear control Consensus},
}

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%0 Journal Article
%T Bipartite consensus control for fractional-order nonlinear multi-agent systems: An output constraint approach
%A Shahvali, Milad
%A AZARBAHRAM, ALI
%A Naghibi Sistani, Mohammad Bagher
%A Javad Askari
%J Neurocomputing
%@ 0925-2312
%D 2020

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