A Fixed-Point Iteration Scheme for Sensitivity-Based Distributed Optimal Control

• 成果类型: Article
• 署名作者: von Esch, Maximilian Pierer; Volz, Andreas; Graichen, Knut
• 署名单位: University of Erlangen Nuremberg
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3505753
• 发表日期: 2025
• 页码: 2778-2785
• 关键词: Heuristic algorithms; CONVERGENCE; Couplings; COSTS; trajectory; sensitivity; Prediction algorithms; optimal control; vectors; Predictive control; Agents and autonomous systems; distributed optimal control; Nonlinear systems; optimization algorithms

摘要

This article presents a sensitivity-based algorithm for distributed optimal control problems (OCP) of multi-agent systems with nonlinear dynamics and state/input couplings, as they arise, for instance, in distributed model predictive control. The algorithm relies on first-order sensitivities to cooperatively solve the distributed OCP in parallel. The solutions to the resulting local OCPs are computed with a fixed-point scheme and communicated within one communication step per algorithm iteration to the neighbors. Convergence results are presented under the inexact minimization of the local OCP. The algorithm is evaluated in numerical simulations for an example system.