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MPC Design

Basic workflow for designing traditional (implicit) model predictive controllers

Model predictive controllers use linear plant, disturbance, and noise models to estimate the controller state and predict future plant outputs. For more information on the structure of model predictive controllers, see MPC Modeling. Using your plant, disturbance, and noise models, you can create a model predictive controller at the command line or with the MPC design tool. See Controller Creation for more information. You can simulate the performance of your controller at the command line or in Simulink®.

  • Model Predictive Control Basics
    Modeling, state estimation, and optimization
  • Controller Creation
    Create model predictive controllers
  • Refinement
    Specify prediction and control horizons, terminal weights and custom constraints, model disturbances
  • Analysis
    Review errors, stability problems and effect of weights on performance, compute closed-loop gain, convert controller for linear analysis
  • Simulation
    Simulate controllers for nonlinear plants at single or across multiple operating points
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