Representing complex designs as system models only tells half the story; the underlying mathematics must be solved to gain a deeper understanding of your system behavior.
The powerful solvers built into Simulink leverage state-of-the-art numerical techniques to handle numerical complexities associated with solving systems that are nonlinear, numerically stiff, and have discontinuities including instantaneous changes in their dynamics. You can analyze simulation results and leverage powerful model analysis tools to ensure robust designs.
Depending on your needs, you can run simulations interactively to analyze and understand your design or systematically for optimizing, testing and verifying your design. Simulation acceleration techniques can help you efficiently complete your simulation tasks by speeding up execution times and by distributing multiple simulations across parallel computing hardware resources.You can incorporate live data into your simulation from instrumentation.
Automatic code generation enables you to reuse your system models for real-time simulations. This lets you test more thoroughly, by starting before hardware is available and by simulating conditions that would be dangerous or costly to examine with the real system.
You can leverage your system model as a test bench for downstream design and verification workflows by connecting to popular third-party simulators, embedded development tools, and development boards. Using the model as a reusable test bench, you can verify your implementation via co-simulation, processor-in-the-loop, and hardware-in-the-loop simulation techniques
You can gain insight into simulation results by using built-in displays and scopes. Alternatively, you can create custom displays using MATLAB® graphical development tools: time and frequency plots, 2D and 3D plots, 3D volume views, and 3D animations. You can also use model analysis tools including model coverage and property proving with assertions and constraints, to rapidly develop robust models early in the design.
By collecting on-site data and running simulations studies with your system models you can efficiently reproduce, diagnose, and resolve customer-reported errors without tying up valuable production hardware systems.