论文标题
关于在参数化NMPC中使用数据驱动的成本函数识别
On the use of Data-Driven Cost Function Identification in Parametrized NMPC
论文作者
论文摘要
在本文中，提出了有关使用成本函数的数据驱动模型的约束非线性模型预测控制（NMPC）设计的可行性进行完整数值研究的框架。尽管这个想法非常重要，但本文提出了使用Python模块在GitHub存储库中自由使用的完整实现。此外，提出了有关通过数据驱动的建模的不同方式的讨论，这是从业者感兴趣的。
In this paper, a framework with complete numerical investigation is proposed regarding the feasibility of constrained Nonlinear Model Predictive Control (NMPC) design using Data-Driven model of the cost function. Although the idea is very much in the air, this paper proposes a complete implementation using python modules that are made freely available on a GitHub repository. Moreover, a discussion regarding the different ways of deriving control via data-driven modeling is proposed that can be of interest to practitioners.
