Using Modeling and Simulation to Test Designs and Requirements

 Modeling is an efficient and cost-effective way to represent a real-world system. A model can represent key aspects of the system, including the underlying requirements, the components, and how those components communicate with one another. The model can be simulated, enabling designers to test designs before hardware is available, or to test conditions that are either difficult or expensive to replicate in the real world. Iterating between modeling and simulation can improve the quality of the system design early, reducing the number of errors found later in the design process.

Despite these advantages, designers who heavily rely on hand coding do not always take full advantage of modeling and simulation. Setting up tests can be difficult and time-consuming, and when separate tools are used for each domain, it can be challenging to obtain a system-level view of the design. As a result, defects that could have been found in the modeling and simulation phase are often found during the implementation phase, when defects are more expensive to fix.

These issues are addressed in Simulink®, a platform for modeling and simulation. Simulink supports not only multidomain modeling but also simulation, with its own set of ordinary differential equation (ODE) solvers. A fundamental advantage of using Simulink is that you can represent different domains, including control systems, state machines, and environmental models, in one model, and then run simulations within Simulink to verify that the model is built correctly. As the simulation runs, you have access to simulation analysis capabilities, such as data displays, state animation, and conditional breakpoints. After the simulation is completed, you can analyze any logged data with MATLAB® scripts and visualization tools.

In this article, we describe a workflow for building a component model from requirements, simulating and testing that component model, and then connecting it to a system-level model for further simulation and testing. To illustrate this workflow we will build and test the fault detection, isolation, and recovery (FDIR) component of the HL-20, a re-entry vehicle designed by NASA to complement the Space Shuttle orbiter. We will connect our component to a system-level model that includes environmental models, flight controls, and guidance, navigation, and controls (GN&C) systems, and then simulate the system-level model to validate its behavior.

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