bat365 Homepage

Sensitivity Analysis

Analyze cost function sensitivity to model parameters using design of experiments (DOE), Monte Carlo, and correlation techniques

Use Sensitivity Analysis to evaluate how the parameters and states of a Simulink^® model influence the model output or model design requirements. You can evaluate your model in the Sensitivity Analyzer, or at the command line. You can speed up the evaluation using parallel computing or fast restart. In the Sensitivity Analyzer, after performing sensitivity analysis, you can export the analysis results to the Parameter Estimator or Response Optimizer apps. To learn more about sensitivity analysis and its applications, see What is Sensitivity Analysis?

Apps

Sensitivity Analyzer

Explore design space and determine most influential model parameters

Functions

expand all

Generate Parameter Samples

Specify Parameter Space

`sdo.ParameterSpace`	Specify probability distributions for model parameters
`sdo.GriddedSpace`	Specify discrete grids of sample values for model parameters (Since R2023a)
`combine`	Combine parameter spaces defined for sensitivity analysis (Since R2023a)
`makedist`	Create probability distribution object
`truncate`	Truncate probability distribution object
`setDistribution`	Set distribution of parameter in `sdo.ParameterSpace` object
`addParameter`	Add parameter to `sdo.ParameterSpace` or `sdo.GriddedSpace` object
`removeParameter`	Remove parameter from `sdo.ParameterSpace` or `sdo.GriddedSpace` object
`setValues`	Set grid values of parameters in gridded parameter space (Since R2023a)

Generate Samples

`sdo.sample`	Generate parameter samples for sensitivity analysis
`sdo.scatterPlot`	Scatter plot of samples
`sdo.SampleOptions`	Parameter sampling options for `sdo.sample`
`sdo.GriddingOptions`	Options for sampling gridded parameters with `sdo.sample` (Since R2023a)

Configure Cost Function

Create Simulation Scenario

sdo.SimulationTest Simulation scenario description

Specify Time-Domain Requirements

`sdo.requirements.SignalBound`	Piecewise-linear amplitude bound
`sdo.requirements.SignalTracking`	Reference signal to track
`sdo.requirements.StepResponseEnvelope`	Step response bound on signal
`sdo.requirements.PhasePlaneEllipse`	Impose elliptic bound on phase plane trajectory of two signals
`sdo.requirements.PhasePlaneRegion`	Impose region bound on phase plane trajectory of two signals

Specify Parameter Requirements

`sdo.requirements.FunctionMatching`	Impose function matching constraint on variable
`sdo.requirements.MonotonicVariable`	Impose monotonic constraint on variable
`sdo.requirements.RelationalConstraint`	Impose relational constraint on pair of variables
`sdo.requirements.SmoothnessConstraint`	Impose bounds on gradient magnitude of variable

Specify Frequency-Domain Requirements

`sdo.requirements.BodeMagnitude`	Bode magnitude bound
`sdo.requirements.ClosedLoopPeakGain`	Closed loop peak gain bound
`sdo.requirements.GainPhaseMargin`	Gain and phase margin bounds
`sdo.requirements.OpenLoopGainPhase`	Nichols response bound
`sdo.requirements.PZDampingRatio`	Damping ratio bound
`sdo.requirements.PZNaturalFrequency`	Natural frequency bound
`sdo.requirements.PZSettlingTime`	Settling time bound
`sdo.requirements.SingularValue`	Singular value bound

Configure Cost Function Evaluation

`sdo.evaluate`	Evaluate cost function for samples
`sdo.EvaluateOptions`	Cost function evaluation options for `sdo.evaluate`
`sdo.OperatingPointSetup`	Set up steady-state operating point computation
`sdo.getParameterFromModel`	Get design variables for optimization
`sdo.getStateFromModel`	Initial state for estimation from Simulink model
`sdo.getModelDependencies`	List of model file and path dependencies
`sdo.setValueInModel`	Set design variable value in model
`evalRequirement`	Evaluate design requirement

Analyze Relation Between Parameters and Design Requirements

`sdo.analyze`	Analyze how model parameters influence cost function
`sdo.AnalyzeOptions`	Analysis options for `sdo.analyze`

Topics

Evaluation Basics

What is Sensitivity Analysis?
Simulink Design Optimization™ software performs global sensitivity analysis.
Generate Parameter Samples for Sensitivity Analysis

Generate random samples of parameter values or specify a grid of values for sensitivity analysis in the Sensitivity Analyzer app or at the MATLAB^® command line.
- Generate Random Parameter Values
- Generate Gridded Parameter Values
Analyze Relation Between Parameters and Design Requirements
Use visual and statistical analysis techniques to analyze the relationship between the parameters and design requirements.
Validate Sensitivity Analysis
Validate sensitivity analysis by checking generated parameter values, evaluation results, and analysis results.
Write a Cost Function
Write a cost function for parameter estimation, response optimization, or sensitivity analysis. The cost function evaluates your design requirements using design variable values.

Apps and Programmatic Workflow

Identify Key Parameters for Estimation (GUI)
This example shows how to use sensitivity analysis to narrow down the number of parameters that you need to estimate when fitting a model.
Identify Key Parameters for Estimation (Code)
This example shows how to use sensitivity analysis to narrow down the number of parameters that you need to estimate to fit a model.
Design Exploration Using Parameter Sampling (GUI)
This example shows how to sample and explore a design space using the Sensitivity Analyzer.
Design Exploration Using Parameter Sampling (Code)
This example shows how to sample and explore a design space.
Explore Design Reliability Using Parameter Sampling (GUI)
This example shows how to use the Sensitivity Analyzer to explore the behavior of a PI controller for a DC motor.
Design Optimization for Robustness to Model Component Tolerances
Use sensitivity analysis and response optimization and to evaluate how well a model satisfies design requirements and optimize design variables in the presence of uncertainties in model parameters.

Steady-State Evaluation

Specify Steady-State Operating Point for Sensitivity Analysis
An operating point of a dynamic system defines the states and root-level input signals of the model at a specific time.

Speed Up Evaluation

Use Parallel Computing for Sensitivity Analysis
Specify model dependencies and use parallel computing for performing sensitivity analysis in the app, or at the command line.
Use Fast Restart Mode During Sensitivity Analysis
This topic shows how to speed up sensitivity analysis using Simulink fast restart.
Use Accelerator Mode During Simulations
Simulink Design Optimization software supports Normal and Accelerator simulation modes.
Store Intermediate Data in the App
How to speed up evaluation in the app by storing intermediate data.

Sensitivity Analyzer Tasks

Specify Parameters for Design Exploration
Select model parameters for sensitivity analysis in the app.
Specify Time-Domain Requirements
Specify time-domain requirements such as signal matching, amplitude bounds, step response bounds, reference signals, elliptical bounds, and custom bounds.
Specify Parameters Requirements
Specify requirements such as monotonic, smoothness, property, and relational constraints on parameters in your model.
Specify Frequency-Domain Requirements
Specify frequency-domain requirements in the Sensitivity Analyzer.
Preprocess Data
Perform preprocessing operations such as removing offsets and filtering the data before you use it.
Create Linearization I/O Sets
Create linearization input/output sets in the Response Optimizer or Sensitivity Analyzer.
Evaluate Design Requirements
Evaluate your design requirements in the Sensitivity Analyzer.
Use Sensitivity Analysis to Configure Estimation and Optimization
Use the results generated in the Sensitivity Analyzer to configure parameter estimation or response optimization.
Interact with Plots in the Sensitivity Analyzer
Plot and interpret parameter set, requirement, result scatter, contour, and tornado plots.

Code Generation

Generate MATLAB Code for Sensitivity Analysis for Design Space Exploration and Evaluation (GUI)
This example shows how to automatically generate a MATLAB function to solve a Sensitivity Analysis evaluation problem.
Generate MATLAB Code for Sensitivity Analysis Statistics to Identify Key Parameters (GUI)
This example shows how to automatically generate a MATLAB function to solve a Sensitivity Analysis statistics problem.