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Distributed optimization for interconnected nonlinear multi-agent systems via output feedback
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DOI：10.1016/j.jfranklin.2024.107035.png)
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Abstract
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In this paper, the distributed optimization for a class of interconnected nonlinear multi-agent systems is considered via output feedback control. The problem is challenging because only the system's output is available. The system's states and optimal values are estimated by two reduced-order filters and an optimal observer, respectively. Then the final optimal algorithm is designed based on a back-stepping method. The convergence analysis is built by using Lyapunov stability and perturbation system theory. Some examples are presented to illustrate the effectiveness of the designed optimal algorithm.
Keywords:
Distributed optimization
Interconnected system
Reduced-order filter
Back-stepping control
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3.7
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