High-level language for numerical computation, visualization, and application development Interactive environment for iterative exploration, design, and problem solving Mathematical functions for linear algebra, statistics, Fourier analysis, filtering, optimization, numerical integration, and solving ordinary differential equations Analyzing and visualizing data using the MATLAB desktop.
Introduction to Matlab - ppt download
Built-in graphics for visualizing data and tools for creating custom plots Development tools for improving code quality and maintainability and maximizing performance Tools for building applications with custom graphical interfaces Functions for integrating MATLAB based algorithms with external applications and languages such as C, Java,. Numeric Computation MATLAB provides a range of numerical computation methods for analyzing data, developing algorithms, and creating models.
Core math functions use processor- optimized libraries to provide fast execution of vector and matrix Available methods include: Linear systems of equations Fourier analysis Eigenvalues and singular values Ordinary differential equations ODEs Sparse matrices MATLAB add-on products provide func- tions in specialized areas such as statistics, You can perform exploratory data analysis to uncover trends, test assumptions, and build descriptive models.
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Add-on products pro- vide capabilities for curve and surface fit- ting, multivariate statistics, spectral analysis, image analysis, system MATLAB provides a high-level language and development tools that let you quickly develop and analyze algorithms and The MATLAB language provides native support for the vector and matrix opera- tions that are fundamental to solving engi- neering and scientific problems, enabling fast development and execution.
With the MATLAB language, you can write programs and develop algorithms faster than with traditional languages because you do not need to perform low- level administrative tasks such as declaring variables, specifying data types, and allo- cating memory. In many cases, the support for You can include common controls such as list boxes, pull-down menus, and The Online Industrial Exhibition.
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Rather than forcing users to implement additional functionality by extensively modifying and extending the GridLAB-D source code, GridLAB-D has implemented a number of ways in which it can programmatically interact with external software packages. This chapter will demonstrate how these interfaces work. These options are enabled when running.
If this option has been correctly set, the output of the. The second portion of the interaction is the variable value exchange. If difficulties in the compiling or use of the link is not behaving properly, check the GridLAB-D forums to see if other users have encountered similar problems.
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For this example, let's do something a little silly and use MATLAB as an energy meter, summing the power flow of one of the batteries in the model at each time step of the GridLAB-D simulation to calculate the total energy transfer. And that's it; that's the only change we need to make. We will still be referring to the specific variable names in the model file as we build the link file but this is the only edit that is needed. The comments in the link file are mostly self-explanatory and additional details can be found on the Matlab link wiki page.
The most important items in our case are:.
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If this last part is not added a confusing error message will be posted when the model is run that does not affect the simulation or its results. The general structure of the file is similar to the last example though there are a few items of note. Each time the function is called, the input variables are appended to a CSV.
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As the graph shows, the simple controller functions as expected, keeping the battery with certain state-of-charge range.