simulink design optimization documentation -凯发k8网页登录

simulink^® design optimization™ provides functions, interactive tools, and blocks for analyzing and tuning model parameters. you can determine the model’s sensitivity, fit the model to test data, and tune it to meet requirements. using techniques like monte carlo simulation and design of experiments, you can explore your design space and calculate parameter influence on model behavior.

simulink design optimization helps you increase model accuracy. you can preprocess test data, automatically estimate model parameters such as friction and aerodynamic coefficients, and validate the estimation results.

to improve system design characteristics such as response time, bandwidth, and energy consumption, you can jointly optimize physical plant parameters and algorithmic or controller gains. these parameters can be tuned to meet time-domain and frequency-domain requirements, such as overshoot and phase margin, and custom requirements.