Compare Requirements and Design Variables Using Spider Plot

This example shows how to use a spider plot to compare requirement evaluations before and after optimizing the response. You can use a similar procedure to compare the values of sets of design variables.

Open the Simulink model and load the pre-configured Response Optimizer App session.

For this example, which uses a distillation column model, the step response requirements are preconfigured and loaded in the model workspace.

Open the distillation model.
```
sys = 'distillation_demo';
open_system(sys)
```
Open the Response Optimizer.
In the Simulink^® model window, from the Apps tab, in the gallery, under Control Systems select Response Optimizer.
Alternatively, click the Response Optimization GUI with preloaded data block in the model and skip the next step.
Load the preconfigured Response Optimizer session.
Click the Response Optimization tab. In the Open Session drop-down list, select Open from model workspace. A window opens where you select the Response Optimizer session to load. Select distillation_optim and click OK.
The preconfigured step response requirements are loaded in the Response Optimizer.

Evaluate the requirement before optimization.

In the Response Optimization tab, click Evaluate Requirements.

A new variable, ReqValues, containing the evaluation of the requirements appears in the Data area.

When optimizing the model response, you create a set of requirements that it must satisfy. If the requirements are violated, meaning that they evaluate to non-negative values, the design variables must be optimized. After the optimization, you can compare the original requirement value with the requirement evaluated using the optimized design variable values.

Plot the requirement value before optimization.

In the Data to Plot list, select ReqValues.
In the Add Plot list, select Spider plot.

The plot has an axis for each edge-and-signal combination defined in the distillation_demo/Desired Step Response check block. Points on each axis represent the violation for that signal-edge combination and the plot connects these points to form a closed polygon representing the initial design. Note that some points are negative, representing satisfied constraints, and some positive, representing violated constraints.

Optimize the model.

Click Optimize.

A new variable, ReqValues1, containing the evaluation of the requirements using the optimized design variables appears in the Data area.

Compare the requirement values before and after optimization.

In the Data to Plot list, select ReqValues1.
In the Add Plot list, select Spider plot 1.

The optimized requirement values, ReqValues1, are all negative or zero, indicating that all the constraints are satisfied.