Simulink Design Optimization
Simulink Design Optimization provides tools to analyze and tune model parameters. You can assess sensitivity, fit models to test data, and optimize parameters to meet design requirements. Techniques like Monte Carlo simulation and Design of Experiments help explore the design space and evaluate parameter influence.
The tool supports data preprocessing, automatic parameter estimation (e.g., friction, aerodynamic coefficients), and result validation to improve model accuracy.
You can also jointly optimize plant parameters and controller gains to enhance system performance, meeting time-domain, frequency-domain, and custom requirements.
Design Optimization Apps
Leverage built-in apps in Simulink to interactively define and solve design optimization problems, including setting design requirements, decision variables, and optimization settings. Generate MATLAB code directly from the apps for deployment or further customization.
Parameter Estimation
Create accurate plant models by automatically estimating parameters and states from test data using the Parameter Estimator app or command-line tools in Simulink.
Response Optimization
Automatically tune model parameters to meet time-domain and frequency-domain design requirements using the Response Optimizer app or command-line tools.
Sensitivity Analysis
Use the Sensitivity Analyzer app to determine which parameters most influence your model’s behavior. Improve parameter estimation and design optimization by selecting better initial conditions. Explore the design space and assess design robustness through Monte Carlo simulations.
Co-Optimization of Plant and Controller Parameters
Simultaneously optimize physical plant parameters and controller or algorithm gains to enhance system performance metrics like response time, bandwidth, and energy efficiency.
Digital Twin Tuning
Automatically adjust the parameters of a deployed digital twin to reflect the asset’s current condition. Implement the parameter estimation workflow using Simulink Compiler for deployment.
Lookup Table Tuning
Optimize lookup tables for applications like battery characterization and gain-scheduled controllers. Apply constraints such as monotonicity and smoothness to ensure desired behavior. Use adaptive lookup tables to efficiently address calibration challenges.
Design Optimization Speed-Up
Accelerate parameter estimation, response optimization, and sensitivity analysis by executing multiple model simulations in parallel with Parallel Computing Toolbox. Enhance the performance of design optimization tasks by leveraging Simulink’s fast restart feature and accelerator simulation mode.
Optimization Solvers
Tackle a wide range of optimization problems—such as mixed-integer, derivative-based, and derivative-free—using solvers like surrogate, fmincon, and pattern search from the Optimization Toolbox and Global Optimization Toolbox.