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Creators/Authors contains: "Parisini, Thomas"

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  1. ; ; ; ; (, 2023 62nd IEEE Conference on Decision and Control)
    The distributed optimization algorithm proposed by J. Wang and N. Elia in 2010 has been shown to achieve linear convergence for multi-agent systems with single-integrator dynamics. This paper extends their result, including the linear convergence rate, to a more complex scenario where the agents have heterogeneous multi-input multi-output linear dynamics and are subject to external disturbances and parametric uncertainties. Disturbances are dealt with via an internal-modelbased control design, and the interaction among the tracking error dynamics, average dynamics, and dispersion dynamics is analyzed through a composite Lyapunov function and the cyclic small-gain theorem. The key is to ensure a small enough stepsize for the convergence of the proposed algorithm, which is similar to the condition for time-scale separation in singular perturbation theory. 
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  2. ; ; ; ; ; ; ; ; ; ; et al (, Annual Reviews in Control)
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  3. ; ; ; ; (, IEEE Transactions on Neural Networks and Learning Systems)
    null (Ed.)
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