Montag, 21.06.2021, 13.00 Uhr

Hardware-in-the-Loop Testing of Industrial Automation Systems Using PLC Languages



Testing industrial controllers such as Programmable Logic Controllers (PLCs) poses specific challenges to the test process. Especially in the context of Cyber-Physical Production System (CPPS) the control systems are subject to continuous reconfiguration. Therefore, it is no longer sufficient to test solely before commissioning, but it must be possible to test existing control systems after their reconfiguration with low effort and to put them back into operation.

Our approach for this is to develop a test environment that allows an efficient and modular test case specification and can therefore be easily adapted to changing environmental conditions. We have chosen Hardware-in-the-Loop (HiL) simulation as the basis for this test environment since not only the control model or control program is included in the test, but also the control hardware. Our architecture uses slightly extended PLC programming languages to specify test cases. Thus, we avoid the change in methodology that occurs when using dedicated test case specification languages and corresponding test environments. Furthermore, we have provided our concept with the possibility of randomized test case generation, such that a large number of test cases can be generated and tested without a tester having to specify them manually.

Our hypothesis is that this will lead to faster and more reliable customizable test cases and thus create the desired agility. The evaluation of our implementation shows that especially developers who are familiar with PLC programming languages can achieve an increase in testing efficiency compared to existing test tools. Furthermore, by randomized testing of Safety Programmable Logic Controllers (Safety PLCs), we show that our test tool can find critical errors in control systems, which would have been found with traditional test methods only to a limited extent.

From these results we conclude that the concept presented here is a valuable addition to existing test methods and well-tailored to the challenges of CPPS.


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