![]() After choosing the model and specifying the sample time of your controller, you can try out different conversion methods to find the one that gives you a better match between the original and converted model. If you already know the name of the task you want to use, you can simply start typing its name in the live script and add the task by selecting it from the suggested list. For that we’ll be using the Convert Model Rate task. Now, we’ll move on to the second step of the workflow to discretize the identified model. This saves you time and eliminates the need to search for the specific MATLAB functions and the different options they can be set up with. As we change some of the parameters here, you see how the appropriate arguments are automatically called by these functions. ![]() You can also enable this feature from the options menu by selecting “controls and code.” This task also lets you adjust parameters of the estimation algorithm, such as the search method and maximum iterations. If you want to see the MATLAB commands that are used by this task, you can display them by clicking the arrow on the bottom of the task. Using the task, we easily estimated a model from measured data without writing any code. If you want, you can rename the identified model in this field here. The increased order of 5 didn’t improve the estimation fit much. Since the task is running automatically, when you change the plant order, you’ll see updated results on the right. If you don’t have the knowledge of the plant order, you can simply try out different values. By clicking this circular icon, you can enable the task to run automatically and update and display the results every time you adjust values within the task. When you select data, it automatically finds the appropriate pre-defined variables from the MATLAB workspace that you can choose in these drop-down menus. As you see here, the Live Editor task lets you interactively specify parameters. Here you’ll find Live Editor tasks from different toolboxes. ![]() To find this task, we’ll go to the Live Editor tab and click task. To work on the first step of this workflow, we’ll use the Estimate State-Space Model task. You can display the output of this code either inline or on the right-hand side of the script. This code here loads and plots the measured plant data. Let’s see how you can use these Live Editor tasks to estimate a state-space model from measured plant data, discretize the identified model, and then design a controller for the discretized plant. Live Editor tasks let you accomplish all the workflow steps in one place, saving you time and eliminating the need of writing code. Let’s say this is the workflow you need to follow to design a controller from measured plant data. In 19b, we introduce Live Editor tasks, which are apps you can add to a live script to perform a specific set of operations. Interactive Control Design Using Live Editor Tasks
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