We provide a novel approach to synthesize controllers for nonlinear continuous dynamical systems with control against safety properties. The controllers are based on neural networks (NNs). To certify the safety property we utilize barrier functions, which are represented by NNs as well. We train the controller-NN and barrier-NN simultaneously, achieving a verification-in-the-loop synthesis. We provide a prototype tool nncontroller with a number of case studies. The experiment results confirm the feasibility and efficacy of our approach.

中文翻译：

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学习具有障碍证书的安全神经网络控制器

我们提供了一种新的方法来合成非线性连续动力系统的控制器，并控制安全特性。控制器基于神经网络 (NN)。为了证明安全性，我们使用了障碍函数，也由神经网络表示。我们同时训练控制器神经网络和屏障神经网络，实现在环验证综合。我们提供了一个原型工具 nncontroller 和许多案例研究。实验结果证实了我们方法的可行性和有效性。