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Simulink. Importing and Exporting Simulation Data, Data Stores and Data Dictionary

Simulink. Importing and Exporting Simulation Data, Data Stores and Data Dictionary

          
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About the Book

Exporting (logging) simulation data provides a baseline for analyzing and debugging a model. Use standard or custom MATLAB functions to generate simulated system input signals and to graph, analyze, or otherwise postprocess the system outputs. Simulation data can include any combination of signal, time, output, state, and data store logging data. Exporting simulation data involves saving signal values to the MATLAB workspace or to a MAT-file during simulation for later retrieval and postprocessing. Exporting data is also known as "data logging" or "saving simulation data." You can have data logged in different formats: Array, Structure, Structure with time, MATLAB timeseries and ModelDataLogs. Exporting simulation data often involves exporting signal data. You can use various approaches for exporting signal data. A Simulink model performs algorithms on input signal data and produces output signals. The model defines what input data to use at the start of simulation and what output to capture at the end of simulation. As you create and simulate your model, you: "Identify Model Signal Data Requirements," "Load Input Signal Data" and "Log Output Signal Data." As you create, debug, and test a model, you can use different sets of input signal data for simulation. You can use logged simulation data as input to another simulation. You can use several options to reduce the amount of data logged during a simulation. Limiting the amount of exported simulation data reduces memory usage and speeds up simulation. However, if you limit the amount of simulation data, the logged data can skip some time steps that are critical for testing and analyzing the model. Simulation of models with many time steps and signals can involve big data that is too large to fit into the RAM of your computer. Such situations include: Logging simulation data (signal logging, outport logging, and state logging), Loading input signal data for simulating a model and Running multiple or parallel simulations. To work with big data for simulations, store the data to persistent storage in a MAT-file. Using big data techniques for simulations requires additional steps beyond what you do when the data is small enough to fit in workspace memory. As you develop a model, consider logging and loading simulation data without using persistent storage unless you discover that your model has big data requirements that overload memory. A data store is a repository to which you can write data, and from which you can read data, without having to connect an input or output signal directly to the data store. Data stores are accessible across model levels, so subsystems and referenced models can use data stores to share data without using I/O ports. Data stores can be useful when multiple signals at different levels of a model need the same global values, and connecting all the signals explicitly would clutter the model unacceptably or take too long to be feasible. Data stores are analogous to global variables in programs, and have similar advantages and disadvantages, such as making verification more difficult. To share data between the instances of a reusable algorithm (for example, a subsystem in a custom library or a reusable referenced model), you can use a data store. A Simulink data dictionary is a persistent repository of data that are relevant to your model. You can also use the base workspace to store design data that are used by your model during simulation. However, a data dictionary provides more capabilities.


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Product Details
  • ISBN-13: 9781986322232
  • Publisher: Createspace Independent Publishing Platform
  • Publisher Imprint: Createspace Independent Publishing Platform
  • Language: English
  • ISBN-10: 1986322238
  • Publisher Date: 16 Dec 2018
  • Binding: Paperback


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