Pierer von Esch M, Völz A, Graichen K (2024)
Publication Language: English
Publication Type: Journal article
Publication year: 2024
This paper presents synchronous as well as asynchronous formulations of the Alternating
Direction Method of Multipliers (ADMM) for solving continuous-time
nonlinear distributed model predictive control (DMPC) problems. It is shown that
the optimal control problems of certain system classes can be transformed to fit the
consensus-based ADMM variant problem formulation. The arising sub-problems
are solved locally on the agent level while the consensus step is solved centrally by
a coordinator. Furthermore, the convergence of the synchronous and asynchronous
ADMM algorithms to their respective first-order optimality conditions is presented
in a continuous-time setting. The algorithm is applied to different example systems
for which the convergence behavior and influence of the individual algorithmic parameters
are investigated. The computation time of the agents remains unaffected
by the system size and thus demonstrates the applicability to high-scaled systems.
Moreover, results show that the asynchronous algorithm performs better in terms of
execution time when compared to its synchronous counterpart.
APA:
Pierer von Esch, M., Völz, A., & Graichen, K. (2024). Asynchronous ADMM for Nonlinear Continuous-Time Systems. Optimal Control Applications & Methods.
MLA:
Pierer von Esch, Maximilian, Andreas Völz, and Knut Graichen. "Asynchronous ADMM for Nonlinear Continuous-Time Systems." Optimal Control Applications & Methods (2024).
BibTeX: Download