24th EANN 2023, 14 - 17 June 2023, León, Spain

Verification of neural networks meets PLC code: An LHC cooling tower control system at CERN

Ignacio D. Lopez-Miguel, Borja Fernández Adiego, Faiq Ghawash, Enrique Blanco Viñuela


  In the last few years, control engineers have started to use artificial neural networks (NNs) embedded in advanced feedback control algorithms. Its natural integration into existing controllers, such as programmable logic controllers (PLCs) or close to them, represents a challenge. Besides, the application of these algorithms in critical applications still raises concerns among control engineers due to the lack of safety guarantees. Building trustworthy NNs is still a challenge and their verification is attracting more attention nowadays. This paper discusses the peculiarities of formal verification of NNs controllers running on PLCs. It outlines a set of properties that should be satisfied by a NN that is intended to be deployed in a critical high-availability installation at CERN. It compares different methods to verify this NN and sketches our future research directions to find a safe NN.  

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