TY - GEN
T1 - Discrete-Time Distributed Optimization for Linear Uncertain Multi-Agent Systems
AU - Liu, Tong
AU - Bin, Michelangelo
AU - Notarnicola, Ivano
AU - Parisini, Thomas
AU - Jiang, Zhong Ping
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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-model-based 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.
AB - 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-model-based 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.
UR - http://www.scopus.com/inward/record.url?scp=85184827489&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85184827489&partnerID=8YFLogxK
U2 - 10.1109/CDC49753.2023.10384140
DO - 10.1109/CDC49753.2023.10384140
M3 - Conference contribution
AN - SCOPUS:85184827489
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 7439
EP - 7444
BT - 2023 62nd IEEE Conference on Decision and Control, CDC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 62nd IEEE Conference on Decision and Control, CDC 2023
Y2 - 13 December 2023 through 15 December 2023
ER -