Which variables hold values that vary during the course of this simulation?
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When you sweep one or more parameters, you change their values between simulation runs, and compare and analyze the output signal data from each run. Use parameter sweeping to tune control parameters, estimate unknown model parameters, and test the robustness of a control algorithm by taking into consideration uncertainty in the real-world system. Show
You can sweep block parameter values or the values of workspace variables that you use to set the parameter values. Use the Parameters tab on the Model Data Editor (on the Modeling tab, click Model Data Editor), the Property Inspector (on the Modeling tab, under Design, click Property Inspector), the command prompt, or scripts to change parameter values between simulation runs. If you want to repeatedly change the value of a block parameter, consider creating a variable in a workspace. You can use the Model Explorer or programmatic commands to change the value of the variable instead of locating or identifying the block in the model. Also, several features and products that facilitate parameter optimization, estimation, and sweeping require that you set block parameter values by creating workspace variables. To learn how to manipulate parameter values during the iterative process of creating a model, see Tune and Experiment with Block Parameter Values. For basic information about accessing and setting block parameter values as you design a model, see Set Block Parameter Values. For basic information about programmatically simulating a model, such as by using a script, see Run Simulations Programmatically. Sweep Parameter Value and Inspect Simulation ResultsThis example shows how to change a block parameter value between multiple programmatic simulation runs. Use this technique to determine an optimal parameter value by comparing the output signal data of each run. The example model relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
3 uses a Constant block to specify a slip setpoint for an anti-lock braking system. Simulate the model with two different slip setpoint values, 0.24 and 0.25, and compare the output wheel speed of each simulation run.To store the setpoint value, create a variable in the base workspace. This technique enables you to assign a meaningful name to the value. Open the example model. open_system('ex_sldemo_absbrake');
 On the Modeling tab, click Model Data Editor. In the Model Data Editor, select the Signals tab. Set the Change view drop-down list to relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
4. The Log Data column shows that the signals relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
5 (which is a virtual bus) and relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
6 are configured for logging. When you simulate the model, you can collect and later inspect the values of these signals by using the Simulation Data Inspector.In the Model Data Editor, select the Parameters tab. Set Change view to relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
7.In the model, select the Constant block labeled relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
8. The Model Data Editor highlights the row that corresponds to the Constant value parameter of the block.Use the Value column to set the parameter value to relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
9.While editing the value, next to relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
9, click the action button (with three vertical dots) and select Create.In the Create New Data dialog box, set Value to relSlip_vals = [0.24 0.25];1 and click Create. A variable, whose value is relSlip_vals = [0.24 0.25];1, appears in the base workspace. The model now acquires the relative slip setpoint from this variable. Alternatively, you can use these commands at the command prompt to create the variable and configure the block: relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
At the command prompt, create an array to store the two experimentation values for the relative slip setpoint, relSlip_vals = [0.24 0.25];3 and relSlip_vals = [0.24 0.25];4. relSlip_vals = [0.24 0.25]; Create a relSlip_vals = [0.24 0.25];5 object for each simulation that you want to run (in this case, two). Store the objects in a single array variable, relSlip_vals = [0.24 0.25];6. Use the relSlip_vals = [0.24 0.25];7 method of each object to identify each of the two experimentation values. for i = 1:length(relSlip_vals)
simIn(i) = Simulink.SimulationInput('ex_sldemo_absbrake');
simIn(i) = setVariable(simIn(i),'relSlip',relSlip_vals(i));
end
Use the relSlip_vals = [0.24 0.25];8 function to simulate the model. Optionally, store the output in a variable named relSlip_vals = [0.24 0.25];9. [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs The model streams the logged signals, relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
5 and relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
6, to the Simulation Data Inspector. You can view the signal data in the Simulation Data Inspector.Compare the output data of the two latest simulation runs. runIDs = Simulink.sdi.getAllRunIDs(); runResult = Simulink.sdi.compareRuns(runIDs(end-1), runIDs(end)); Plot the difference between the values of the for i = 1:length(relSlip_vals)
simIn(i) = Simulink.SimulationInput('ex_sldemo_absbrake');
simIn(i) = setVariable(simIn(i),'relSlip',relSlip_vals(i));
end
2 signal (which is an element of the virtual bus signal relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
5) by specifying the result index for i = 1:length(relSlip_vals)
simIn(i) = Simulink.SimulationInput('ex_sldemo_absbrake');
simIn(i) = setVariable(simIn(i),'relSlip',relSlip_vals(i));
end
4.signalResult = getResultByIndex(runResult,1); plot(signalResult.Diff); Store Sweep Values in relSlip_vals = [0.24 0.25]; 5 ObjectsWhen you write a script to run many simulations, create an array of relSlip_vals = [0.24 0.25];5 objects (one object for each simulation that you want to run). Use the relSlip_vals = [0.24 0.25];7 and for i = 1:length(relSlip_vals)
simIn(i) = Simulink.SimulationInput('ex_sldemo_absbrake');
simIn(i) = setVariable(simIn(i),'relSlip',relSlip_vals(i));
end
8 methods of each object to identify the parameter values to use for the corresponding simulation run. With this technique, you avoid having to use the for i = 1:length(relSlip_vals)
simIn(i) = Simulink.SimulationInput('ex_sldemo_absbrake');
simIn(i) = setVariable(simIn(i),'relSlip',relSlip_vals(i));
end
9 function to modify block parameter values and assignment commands to modify workspace variable values between simulation runs.For more information about using relSlip_vals = [0.24 0.25];5 objects to run multiple simulations, see relSlip_vals = [0.24 0.25];8. Sweep Nonscalars, Structures, and Parameter ObjectsIf you use nonscalar variables, structure variables, or [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs2 objects to set block parameter values, use the relSlip_vals = [0.24 0.25];7 method of each relSlip_vals = [0.24 0.25];5 object. Refer to the examples in the table. ScenarioExampleMATLAB® variable, [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs5, whose value is an array. You want to set the third element in the array (assuming one-based indexing). setVariable(simIn,'myArray(3)',15.23)MATLAB variable, [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs6, that has a field named [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs7. setVariable(simIn,'myStruct.field1',15.23)Parameter object, [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs8, whose [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs9 property is a scalar. setVariable(simIn,'myParam.Value',15.23)Parameter object, runIDs = Simulink.sdi.getAllRunIDs(); runResult = Simulink.sdi.compareRuns(runIDs(end-1), runIDs(end));0, whose [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs9 property is an array. You want to set the third element in the array. relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
0Parameter object, runIDs = Simulink.sdi.getAllRunIDs(); runResult = Simulink.sdi.compareRuns(runIDs(end-1), runIDs(end));2, whose [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs9 property is a structure. The structure has a field named [26-Nov-2022 09:53:03] Running simulations... [26-Nov-2022 09:53:04] Completed 1 of 2 simulation runs [26-Nov-2022 09:53:05] Completed 2 of 2 simulation runs7. relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
1Sweep Value of Variable in Model WorkspaceIf you use the model workspace to store variables, when you use the relSlip_vals = [0.24 0.25];7 method of a relSlip_vals = [0.24 0.25];5 object to modify the variable value, use the runIDs = Simulink.sdi.getAllRunIDs(); runResult = Simulink.sdi.compareRuns(runIDs(end-1), runIDs(end));7 pair argument to identify the containing model: relSlip = 0.2;
set_param('ex_sldemo_absbrake/Desired relative slip','Value','relSlip')
2Capture and Visualize Simulation ResultsEach simulation run during a parameter sweep produces outputs, such as signal values from Outport blocks and from logged signals. You can capture these outputs in variables and objects for later analysis. For more information, see Export Simulation Data. To visualize simulation output data so you can compare the effect of each parameter value, see Decide How to Visualize Simulation Data. Improve Simulation SpeedTo perform many simulations that each use different parameter values, you can use accelerated simulation modes. For larger models, accelerated simulations take less time to execute than normal simulations. If you also have Parallel Computing Toolbox™, you can use the multiple cores of your processor to simultaneously execute simulations. Use arguments of the relSlip_vals = [0.24 0.25];8 and runIDs = Simulink.sdi.getAllRunIDs(); runResult = Simulink.sdi.compareRuns(runIDs(end-1), runIDs(end));9 functions. To improve the simulation speed of your model by using accelerated simulations and other techniques, see Optimize Performance. For examples and more information, see Running Multiple Simulations. Sweep Parameter Values to Test and Verify SystemIf you have Simulink® Test™, you can confirm that your model still meets requirements when you use different parameter values. Parameter overrides and test iterations enable you to set different parameter values for each test case. For more information, see (Simulink Test) and Test Iterations (Simulink Test). Estimate and Calibrate Model ParametersIf you have Simulink Design Optimization, you can optimize control parameter values so that simulation outputs meet response requirements that you specify. For more information, see Design Optimization to Meet Step Response Requirements (GUI) (Simulink Design Optimization). What is a simulation choose 1 answer?A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time.
What term is used to describe an object that changes in state throughout the course of a simulation?Q1: What term is used to describe an object that changes in state throughout the course of a simulation? MULTI-STATE.
What is simulation stage?The simulation stage of Android system testing consists of running an entire application with programmatically described test cases in an isolated environment on an emulated device.
Which of the following is the order of simulation methodology?Which of the following is the order of simulation methodology? Define the problem, Construct the simulation model, Test and validate the model, Design the experiment, Conduct the experiment, Evaluate the results, Implement the results.
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