Learning Safe Neural Network Controllers with Barrier Certificates

Hengjun Zhao; Xia Zeng; Taolue Chen; Zhiming Liu; Jim Woodcock

Learning Safe Neural Network Controllers with Barrier Certificates

Hengjun Zhao, Xia Zeng, Taolue Chen, Zhiming Liu, Jim Woodcock

Computer Science

Research output: Working paper › Preprint

Abstract

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.

Original language	Undefined/Unknown
Publication status	Published - 18 Sept 2020

Keywords

eess.SY
cs.AI
cs.LG
cs.SY

Access to Document

2009.09826v1

Cite this

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