Automated generation of simulation models for control code tests

Abstract The correct configuration of the control code is a critical part of every process control system engineering project. To ensure the conformity of the implemented control functions with the customer’s specifications, test activities, e.g., the factory acceptance test (FAT), are conducted in every control engineering project. For the past several years, control code tests have increasingly been carried out on simulation models to increase test coverage and timeliness. Despite the advantages that simulation methods offer, the manual effort for generating an applicable simulation model is still high. To reduce this effort, an automated model generation is proposed in this paper. The models automatically generated by this approach provide a modeling level of detail that matches the requirements for the tests of the control code on the base automation level. Therefore, these models do not need to be as detailed as the high-fidelity models which are used for, e.g., model predictive control (MPC) applications. Within this paper, the authors describe an approach to automatically generate simulation models for control code tests based on given computer aided engineering (CAE) planning documents.