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 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 and uses the concept of neighbor approximation to enhance convergence speed. The presented framework can be accessed through C++ and Python and also supports plug-and-play and data exchange between agents over a network.

中文翻译：

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非线性连续时间系统的分布式模型预测控制的模块化框架（GRAMPC-D）

本文提出了用于分布式系统模型预测控制的模块化开源框架GRAMPC-D。模块化的概念允许使用相同的问题描述以集中和分布式的方式解决最佳控制问题。它针对嵌入式硬件的计算效率进行了量身定制。分布式解决方案基于乘法器的交替方向方法，并使用邻居逼近的概念来提高收敛速度。所提供的框架可以通过C ++和Python访问，并且还支持即插即用以及通过网络在代理之间进行数据交换。