Specify design variables, progress plots and methods,
speed up optimization using parallel computing and fast restart, incorporate
parameter uncertainty for robustness testing

Response Optimization Tool | Optimize model response to satisfy design requirements, test model robustness |

`sdo.SimulationTest` |
Simulation scenario description |

`sdo.setValueInModel` |
Set design variable value in model |

`sdo.getValueFromModel` |
Get design variable value from model |

`sdo.optimize` |
Design optimization problem solution |

`sdo.OptimizeOptions` |
Optimization options |

`sdo.getParameterFromModel` |
Design variable for optimization |

`sdo.getModelDependencies` |
List of model file and path dependencies |

**Design Optimization to Meet Step Response Requirements (GUI)**

Optimize controller parameters using the Response Optimization tool.

**Design Optimization to Meet Step Response Requirements (Code)**

Optimize controller parameters at the command line.

**Design Optimization to Track Reference Signal (GUI)**

Optimize parameters without adding Signal Constraint blocks to the model.

**Design Optimization to Meet Frequency-Domain Requirements (GUI)**

This example shows how to tune model parameters to meet frequency-domain requirements using the Response Optimization tool.

**Design Optimization to Meet Frequency-Domain Requirements (Code)**

This example shows how to tune model parameters to meet frequency-domain requirements, using the `sdo.optimize`

command.

**Design Optimization Using Frequency-Domain Check Blocks (GUI)**

Optimize model parameters to meet frequency-domain design requirements using the Response Optimization tool.

**Design Optimization to Meet Time- and Frequency-Domain Requirements (GUI)**

This example shows how to tune a controller to satisfy time- and frequency-domain design requirements using the Response Optimization tool.

Write a cost function for parameter estimation, response optimization, or sensitivity analysis. The cost function evaluates your design requirements using design variable values.

**Design Optimization to Meet a Custom Objective (GUI)**

This example shows how to optimize a design to meet a custom objective using the Response Optimization tool.

**Design Optimization to Meet a Custom Objective (Code)**

This example shows how to optimize a design to meet custom objective using `sdo.optimize`

.

**Design Optimization to Meet Custom Signal Requirements (GUI)**

This example shows how to optimize a design to meet a custom signal requirement.

**Specify Custom Signal Objective with Uncertain Variable (GUI)**

This example shows how to specify a custom objective function for a model signal.

**Optimizing Parameters for Robustness**

A design is *robust* when its response does not violate design requirements under model parameter variations.

**Specify Custom Signal Objective with Uncertain Variable (GUI)**

This example shows how to specify a custom objective function for a model signal.

**Design Optimization with Uncertain Variables (Code)**

This example shows how to optimize a design when there are uncertain variables.

**Skip Model Simulation Based on Parameter Constraint Violation (GUI)**

This example shows how to optimize a design and specify parameter-only constraints that prevent the model from being evaluated in an invalid solution space.

**Speed Up Response Optimization Using Parallel Computing**

Scenarios when you can speed up optimization using parallel computing, and how the speedup happens.

**Use Parallel Computing for Response Optimization**

Use parallel computing for response optimization in the tool, or at the command line.

**Optimizing Time-Domain Response of Simulink® Models Using Parallel Computing**

This example shows how to use parallel computing to optimize the time-domain response of a Simulink® model.

**Use Fast Restart Mode During Response Optimization**

This topic shows how to speed up response optimization using Simulink^{®} fast restart.

**Use Accelerator Mode During Simulations**

Simulink Design Optimization™ software supports `Normal`

and `Accelerator`

simulation modes.

This topic shows how to specify design variables for optimization.

This topic shows how to specify signals to log.

This example shows how to create a linearization input/output set in the Response Optimization tool or Sensitivity Analysis tool.

This topic shows how to specify optimization options in the Response Optimization tool, after you have configured the design variables and design requirements.

This topic shows how to interact with plots in the Response Optimization tool.

**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.

**Save Design Variable Values for Specific Iteration**

This example shows how to save the design variable values for specific optimization iterations.

**Update Model with Design Variables Set**

This example shows how to update a model with a set of design variables.

**Save and Load Optimization Sessions**

This topic shows how to save and load optimization sessions in the Response Optimization tool.

**Generate MATLAB Code for Design Optimization Problems (GUI)**

This example shows how to automatically generate a MATLAB function to solve a Design Optimization problem.

**Optimization Does Not Make Progress**

What to do if the optimization stalls or no changes are seen in parameters values.

What to do if the optimization does not satisfy design requirements or takes a long time to converge near a solution, or if the system response becomes unstable.

**Optimization Speed and Parallel Computing**

What to do if no speedup is seen with parallel computing, if the results are different, or if the optimization stalls.

What to do if optimization gives undesirable parameter values or violates bounds on values.

**Reverting to Initial Parameter Values**

How to quit optimizing and revert to original values.

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