Simulink Design Optimization

Accounting for Parameter Variation or Uncertainty

Simulink Design Optimization lets you test the robustness of your design against variations in model parameters. You can use Monte Carlo simulations to improve the robustness of designs involving uncertain parameters. Simulink Design Optimization lets you set nominal and bounding values for each uncertain parameter in the model.

Using Simulink Design Optimization, you can check the effects of parameter variations and uncertainty on system response and account for these effects during optimization.

Tuning the parameters associated with a PID Controller block in the presence of parameter uncertainty in a Plant block.
Tuning the parameters associated with a PID Controller block (top, blue) in the presence of parameter uncertainty (bottom left) in a Plant block (top, pink). The step response and reference tracking plots (bottom right) show nominal response (solid blue line) and response with uncertainty (dashed blue lines).

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Modellierung elektrischer Systeme einfach gemacht - Systemoptimierung und Reglerentwurf mit Simulink

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