A model predictive controller uses linear plant, disturbance, and noise models to estimate the controller state and predict future plant outputs. Using the predicted plant outputs, the controller solves a quadratic programmingoptimization problemto determine optimal manipulated variable adjustments. For more information on the structure of model predictive controllers, seeMPC Prediction Models. Using your plant, disturbance, and noise models, you can create an MPC controller using theMPC设计erapp or at the command line. You can simulate the performance of your controller at the command line or in Simulink^®.