Simulink Design Optimization 1.1

Working with Simulink Design Optimization

With Simulink Design Optimization, you can calibrate model parameters with test data and tune model parameters to meet design requirements. Simulink Design Optimization uses a Control and Estimation Tools Manager GUI to help you configure, manipulate, and run your Simulink optimization problem. You can work directly with Simulink models that include nonlinear effects, multiple sampling rates, or fixed-point calculations. Models using any blocks from Simulink and add-on products are supported.

You can optimize multiple model parameters at the same time. The parameters can be scalars, vectors, matrices, or fields of structured variables defined in the MATLAB® or model workspace.

Simulink Design Optimization gives you access to a variety of optimization algorithms: gradient descent, nonlinear least squares, simplex search, and pattern search (with Genetic Algorithm and Direct Search Toolbox™). You can fine-tune optimization performance by adjusting optimization algorithm settings, such as convergence tolerances and number of iterations. You can use Simulink Design Optimization in conjunction with Parallel Computing Toolbox™ to accelerate the optimization process.

Control and Estimation Tools Manager GUI for configuring, manipulating, and running optimization problems. In this example, the parameters with check marks have been selected for estimation. Click on image to see enlarged view.