论文标题
学习控制工程应用程序的数据驱动的PCHD模型
Learning Data-Driven PCHD Models for Control Engineering Applications
论文作者
论文摘要
控制工程应用程序的设计通常需要一个准确代表真实系统动态的模型。除了经典的物理建模外，还越来越多地使用强大的数据驱动方法。但是，所得模型不一定是对控制器设计有利的形式。在控制工程领域中，如果以PCHD形式（端口控制的汉密尔顿系统具有耗散）给出系统动态，则非常有益，因为在保证物理解释性的情况下可以轻松实现全球稳定的控制法律。在这项工作中，我们利用了策略的优势，并提出了一个新框架，以直接以PCHD形式的数据驱动方式获得非线性高准确的系统模型。我们通过在学术示例上以及在测试床上进行实验的示例中通过基于模型的应用来证明我们方法的成功。
The design of control engineering applications usually requires a model that accurately represents the dynamics of the real system. In addition to classical physical modeling, powerful data-driven approaches are increasingly used. However, the resulting models are not necessarily in a form that is advantageous for controller design. In the control engineering domain, it is highly beneficial if the system dynamics is given in PCHD form (Port-Controlled Hamiltonian Systems with Dissipation) because globally stable control laws can be easily realized while physical interpretability is guaranteed. In this work, we exploit the advantages of both strategies and present a new framework to obtain nonlinear high accurate system models in a data-driven way that are directly in PCHD form. We demonstrate the success of our method by model-based application on an academic example, as well as experimentally on a test bed.
