Alec Stothert, MathWorks
Many design problems involve performance and cost tradeoffs where the cost can be measured in dollars, weight, or footprint size. Using a Simulink® model of speed control for an engine, this recorded webinar shows how to use Simulink Design Optimization to analyze and solve this type of tradeoff problem. Specifically we will tackle a design tradeoff relating sensor accuracy, actuator response, and controller discretization to control performance.
Through demonstrations and examples you will learn:
• How to use simulation to optimize design tradeoffs and performance specifications simultaneously
• How to select optimization options when using Simulink Design Optimization
• How to tune variables in a model to meet any performance or system specifications
Simulink Design Optimization helps you tune design parameters in Simulink models by optimizing time-based signals to meet user-defined constraints. It optimizes scalar, vector, and matrix-type variables, and constrains multiple signals at any level in the model. Simulink Design Optimization supports continuous, discrete, and multirate models, and enables you to account for model uncertainty by conducting Monte Carlo simulations.
Recorded: 1 Apr 2009