Managin Blocks in Simulink (Paperback) | Released: 07 Mar 2018

When creating models, you need to be aware that Simulink blocks fall into two basic categories: nonvirtual blocks and virtual blocks. Nonvirtual blocks play an active role in the simulation of a system. If you add or remove a nonvirtual block, you change the model's behavior. Virtual blocks, by contrast, play no active role in the simulation; they help organize a model graphically. Some Simulink blocks are virtual in some circumstances and nonvirtual in others. Such blocks are called conditionally virtual blocks. For each block in a model, you can set general block properties, such as: A description of the block, The block execution order, A block annotation and Block callback functions. To set block properties, use the Property Inspector. You can set properties in the Properties and Info tabs of the Property Inspector when the block is selected. Alternatively, you can use the Block Properties dialog box. In the Property Inspector, use the Block Annotation section to display the values of selected block parameters in an annotation. The annotation appears below the block icon. Enter the text of the annotation in the text box. You can use a block property token in the annotation. The value for the property replaces the token in the annotation in the model. Use the Callbacks section to specify block callbacks. Callbacks are MATLAB commands that execute when a specific model action occurs, such as when you select or delete a block. Blocks have numeric parameters that determine how they calculate output values. To control the calculations that blocks perform, you can specify parameter values. For example, a Gain block has a Gain parameter, and a Transfer Fcn block has multiple parameters that represent the transfer function coefficients. You can use numbers, variables, and expressions to set block parameter values. Choose a technique based on your modeling goals. For example, you can: Share parameter values between blocks and models by creating variables, Control parameter characteristics such as data type and dimensions by creating parameter objects and Model an algorithm as code by using mathematical expressions. As you construct a model you can experiment with block parameters, such as the coefficients of a Transfer Fcn block, to help you decide which blocks to use. You can simulate the model with different parameter values, and capture and observe the simulation output. You can change the values of most numeric block parameters during a simulation. To observe the effects, you can visualize the simulation output in real time. This technique allows you to quickly test parameter values while you develop an algorithm. You can visually: Tune and optimize control parameters, Calibrate model parameters and Test control robustness under different conditions. When you begin a simulation, Simulink first updates the model diagram. This operation can take time for larger models. To test parameter values without repeatedly updating the model diagram, you can tune the parameter values during a single simulation run. Alternatively, to avoid updating the model diagram, use Fast Restart. In Simulink you can mask blocks. When you mask a block, a mask definition is created and saved along with the block. In Simulink you can create your own blocks to extend the built-in modeling functionality. To summarize, integrate existing code if you already have code that you would like to access in Simulink. If you do not have existing code, but have a particular functionality that Simulink does not satisfy, create your own block. You can create instances of blocks from installed Simulink libraries, and you can create custom libraries to create and maintain instances of your own blocks in models. A block library is a collection of blocks that you can use to create instances of those blocks in a Simulink model.