Simulink. Analyzing Simulink Results and Improving Simulation Performance (Paperback) | Released: 16 Dec 2018

In Simulink during the modeling process, you run simulations to learn about the behavior of your model. To observe that behavior, view and plot signal values during and after a simulation. Some common modeling tasks that include simulations are: Prototype (Quickly model a design and compare design alternatives), Validate (Compare simulated data with functional requirements to validate that you built your model correctly), Optimize (Compare simulated data between simulations to check if changes to your model remain within a specified design tolerance) and Verify (Compare simulated data from a model with measured data from the modeled system to verify that your model gives the correct answer). In Simulink you can view simulation data using several approaches. Some approaches display signal data during a simulation. Other approaches save signal data to the MATLAB workspace where you can post process the data. Learn about each of these approaches so you can choose one suitable for your application. If you run your simulation more than once and want to inspect or compare data between simulations, you can use the Simulation Data Inspector. You can stream and store signals from the model and compare data between multiple simulations. Create an interactive display of controls and displays within your model diagram using blocks from the Dashboard library. Connect block parameters to control blocks (Knobs, Buttons, and Switches) and signals to displays blocks. (Scopes and Gauges). Use Outport blocks to save simulation data from the top-level of your model to the MATLAB workspace. Select and define the variables for saving data in the Data Import/Export pane of the Configuration Parameters dialog box. Use To Workspace blocks to save simulation data from anywhere in your model to the MATLAB workspace. Store a time vector by connecting a Clock block to a To Workspace block. You can also get a time vector using the sim command. In Simulink you can also use Optimization Techniques to Improve Performance and Accuracy in models. The design of a model and choice of configuration parameters can affect simulation performance and accuracy. Solvers handle most model simulations accurately and efficiently with default parameter values. However, some models yield better results when you adjust solver parameters. Information about the behavior of a model can help you improve simulation performance, particularly when you provide this information to the solver. Use optimization techniques to better understand the behavior of your model and modify the model settings to improve performance and accuracy. When model simulation slows down or stops responding, a close examination of the dynamics of the model can help you identify the factors affecting the simulation. Understanding solver behavior enables you to interpret how the model simulates and what causes the solver to take small steps. The Solver Profiler analyzes a model for patterns that affect its simulation. The Solver Profiler presents graphical and statistical information about the simulation, solver settings, events, and errors. You can use this data to identify locations in the model that caused simulation bottlenecks. The debugger has both a graphical and a command-line user interface. The graphical interface allows you to access the most commonly used features of the debugger. The command-line interface gives you access to all of the capabilities in the debugger. Simulink also includes acceleration mode. Acceleration is a mode of operation in the Simulink product that you can use to speed up the execution of your model. The Simulink software ncludes two modes of acceleration: accelerator mode and the rapid accelerator mode.