论文标题
非线性连续时间系统（GRAMPC-D）的分布式模型预测控制的模块化框架
A Modular Framework for Distributed Model Predictive Control of Nonlinear Continuous-Time Systems (GRAMPC-D)
论文作者
论文摘要
本文介绍了用于分布式系统模型预测控制的模块化开源框架GRAMPC-D。模块化概念允许使用相同的问题描述以集中和分布的方式解决最佳控制问题（OCP）。它针对计算效率量身定制，重点是嵌入式硬件。分布式解决方案基于乘数的交替方向方法（ADMM），并使用邻居近似的概念来增强收敛速度。可以通过CPP和Python访问提出的框架，还可以通过网络通过网络之间的插件和数据交换。
The modular open-source framework GRAMPC-D for model predictive control of distributed systems is presented in this paper. The modular concept allows to solve optimal control problems (OCP) in a centralized and distributed fashion using the same problem description. It is tailored to computational efficiency with the focus on embedded hardware. The distributed solution is based on the Alternating Direction Method of Multipliers (ADMM) and uses the concept of neighbor approximation to enhance convergence speed. The presented framework can be accessed through Cpp and Python and also supports plug-and-play and data exchange between agents over a network.
