LPV Scheme for Robust Adaptive Output Feedback Consensus of Lipschitz Multiagents Using Lipschitz Nonlinear Protocol
In: IEEE Transactions on Systems, Man, and Cybernetics: Systems, Jg. 51 (2021-11-01), S. 7040-7050
Online
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Zugriff:
This article addresses the robust nonlinear adaptive consensus protocol design approach, for nonlinear multiagent (MA) systems under external perturbations with Lipschitz dynamics. Based on the existing results of the adaptive protocol using relative output information, a modified robust nonlinear adaptive consensus protocol for MAs is proposed. The Lipschitz nonlinearity in the agents’ dynamics and the adaptive protocol are reformulated using a composite linear parameter-varying (LPV) approach. Our composite LPV reformulation is less restrictive because it utilizes all the properties of Lipschitz functions. Consensus protocol design conditions based on the proposed reformulation of Lipschitz nonlinearities, Lyapunov theory, and the modified nonlinear consensus protocol are derived to attain the exponential consensus. The proposed consensus protocol approach is further extended by providing necessary and sufficient conditions for the straightforward evaluation of the robust adaptive protocol gains. The proposed fully distributed consensus protocol is robust to ensure the consensus error and adaptive gains bounded by eliminating the effect of disturbances. The resultant consensus control scheme reduces conservatism and is feasible for large values of Lipschitz constants. Finally, simulation results are presented for verifying the potency of the developed control strategies.
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LPV Scheme for Robust Adaptive Output Feedback Consensus of Lipschitz Multiagents Using Lipschitz Nonlinear Protocol
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Autor/in / Beteiligte Person: | Iqbal, Naeem ; Ateeq ur Rehman ; Rehan, Muhammad ; Choon Ki Ahn |
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Zeitschrift: | IEEE Transactions on Systems, Man, and Cybernetics: Systems, Jg. 51 (2021-11-01), S. 7040-7050 |
Veröffentlichung: | Institute of Electrical and Electronics Engineers (IEEE), 2021 |
Medientyp: | unknown |
ISSN: | 2168-2232 (print) ; 2168-2216 (print) |
DOI: | 10.1109/tsmc.2020.2964567 |
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