Simulink Design Optimization 1.1.1

Meeting Design Requirements

With Simulink Design Optimization, you can tune nonlinear Simulink model parameters to meet time-domain requirements and optimize compensators for linear systems to meet both time- and frequency-domain requirements.

Tuning the response of a nonlinear model. The Signal Constraint block (top, red) adjusts the parameters of the Digital Controller block (top, blue) to produce the desired response (tuning progress shown left).

Tuning Simulink Model Parameters to Meet Time-Domain Requirements

Simulink Design Optimization lets you automatically tune model parameters to meet time-domain requirements. You can optimize any design criterion by expressing it as a Simulink signal and connecting this signal to the Signal Constraint block provided by Simulink Design Optimization. The Signal Constraint block lets you constrain the signal by either graphically shaping the desired response or specifying a reference signal trajectory. It then adjusts values of chosen model parameters to satisfy the constraints. The Signal Constraint block GUI updates during optimization so that you can visually monitor the optimization progress. You can use several Signal Constraint blocks simultaneously to optimize multiple design criteria.

Tuning the response of a linearized model to simultaneously meet frequency-domain (above, left) and time-domain (top) requirements (yellow).

Optimizing Compensators to Meet Time- and Frequency-Domain Requirements

Linear compensator design often involves tradeoffs among requirements for stability, robustness, and performance. Simulink Design Optimization lets you account for these tradeoffs as you fine-tune compensators that have been designed with Control System Toolbox and Simulink Control Design™.

You can specify a variety of time- and frequency-domain requirements to optimize the controller performance. Typical requirements include gain and phase margins, damping ratio, minimum bandwidth, high-frequency rolloff, and constraints on the step or impulse responses. You can optimize the poles, zeros, and gains of your compensators, or directly tune the parameters of the corresponding blocks in Simulink. Plots comparing the current response with your design requirements help you monitor progress while the optimization runs.

Specifying Model Uncertainty

Simulink Design Optimization helps you test the robustness of your design against variations in model parameters. You can use either Monte Carlo or fixed-grid simulations to improve the robustness of designs involving uncertain parameters. Simulink Design Optimization also enables you to set nominal and bounding values for each uncertain parameter in the model.

Tuning the parameters associated with the PID Controller block (top, blue) in the presence of parameter uncertainty (left) in the Plant block (top, pink). The step response specifications (right) include design constraints (yellow), reference signal (gray), initial response with uncertainty (solid and dotted blue lines), and final response with uncertainty (solid and dotted black lines).