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Session: Session 16; Digital engineering III
Session starts: Thursday 29 June, 09:00
Presentation starts: 09:40
Room: Theatre room: plenary

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Shawn You (MTS Systems)
Shawn Gao (MTS Systems)

Abstract:
In order to reduce the huge research cost and shorten the lengthy development cycle caused by design iterations, the Model-Based System Engineering (MBSE) method is introduced across the industry. Researchers are trying to use advanced testing and simulation methods, such as virtual testing and model assisted testing to accelerate the development process. Before physical testing, virtual testing can be conducted to simulate the physical test. Virtual model of the full testing system including controller, actuators, test article, and fixtures can be constructed and validated. Virtual testing can provide valuable insight of the real test system such as test system capability, desired PID tuning values, and system controllability. The virtual testing models can be implemented in MBSE models so that the system models can be more accurate. During tests, analysis models can be run in parallel with the test predicting the specimen behavior and guide physical tests in real-time. This approach is called model assisted testing. Model Assisted Compensator (MAC) was developed in this principal and was proven to be effective in compensating the cross coupling effect and achieving accurate control and speeding up the fatigue tests. In this study, a 4-channel test system was used to show the virtual testing process and the effectiveness of MAC. A virtual test model mimicking the physical test system was created and validated. This high-fidelity virtual test system not only could predict the test results, but also, in some instances, help identifying the root-cause of system instabilities. Based upon this model, MAC was created and utilized in a fatigue test. It had been demonstrated that MAC allowed the test to run fast enough that the test article inertia became the limiting factor. Even under complex load control, the transition from one loading stiffness to another can be applied with ease. This model-based approach is scalable to accommodate large scale testing with tens or even hundreds of actuators and complicated dynamic cross coupling.