This example shows how to optimize a design to meet a custom signal requirement. You optimize the controller parameters to minimize the plant actuation signal energy while satisfying step response requirements.
Load a saved Response Optimization tool session.
load sldo_model1_custom_signal_session sdotool(SDOSessionData);
The following Simulink® model opens.
The Response Optimization tool, configured with the following settings, also opens:
Step response characteristics, specified on the output
Plant block, that the model output must
Maximum overshoot of 5%
Maximum rise time of 10 seconds
Maximum settling time of 30 seconds
Design variable set with the controller parameters
These parameters have a minimum value of 0.
The variables for step requirements (
logged signal (
PlantOutput) and design variables
DesignVars) which appear in the Data area.
Specify a signal to log. You apply the custom requirement on this logged signal.
Select New > Signal.
A window opens where you select a signal to log.
In the Simulink model window, click the output
The window updates to display the selected signal.
Select the signal and click to add it to the signal set.
In Signal set, enter
Click OK. A new variable
in the Data area.
Specify the custom requirement to apply to the signal.
The custom requirement calls the objective function
returns the energy in the
The signal energy is minimized. This function accepts:
An input argument
data which is
a structure with fields for the design variables in the Data area.
Signals are logged for the nominal and uncertain parameter values
if there are any.
Returns the objective value to be minimized.
To see the contents of this function, type
Select New > Custom Requirement.
A window opens where you specify the custom requirement.
MinimizeEnergy as the Name.
Minimize the function output as
In the Select Signals and Systems to Bound area,
PlantActuator check box to associate
the custom requirement with that signal.
Click OK. A new variable appears in the Data area of the tool. The window also updates to graphically display the custom signal requirement.
After a few iterations, the optimization converges to meet both the custom signal and step response requirements.
Close the model.