Documentation

Simulink Design Optimization

Estimate and optimize Simulink model parameters

Simulink® Design Optimization™ provides interactive tools, functions, and Simulink blocks for estimating and tuning Simulink model parameters using numerical optimization. An interactive tool lets you automatically estimate model parameters such as friction and aerodynamic coefficients from test data to increase model accuracy. You can preprocess test data, select model parameters to estimate, start an optimization, and validate estimation results.

You can also automatically tune design parameters in a Simulink model to meet objectives such as improved system performance and minimized energy consumption. Using design optimization techniques, you can meet both time- and frequency-domain constraints such as overshoot and phase margin. You can also jointly optimize physical plant parameters and algorithmic or controller gains to maximize overall system performance.

Parameter Estimation

Estimate model parameters and initial states from data, calibrate models

Response Optimization

Optimize model response to satisfy design requirements, test model robustness

Sensitivity Analysis

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

Optimization-Based Control Design

Design controllers using numerical optimization techniques

Lookup Table Estimation

Estimate table data and adaptive lookup tables