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Adaptive MPC Design

Adaptive control of nonlinear plant by updating internal plant model at run time

Adaptive MPC controllers adjust their prediction model at run time to compensate for nonlinear or time-varying plant characteristics. To implement adaptive MPC, first design a traditional model predictive controller for the nominal operating conditions of your control system, and then update the plant model and nominal conditions used by the MPC controller at run time. For more information, see Adaptive MPC. After updating, the plant model and nominal conditions remain constant over the prediction horizon.

If you can predict how the plant and nominal conditions vary in the future, you can use time-varying MPC to specify a model that changes over the prediction horizon. Such a linear time-varying model is useful when controlling periodic systems or nonlinear systems that are linearized around a time-varying nominal trajectory. For more information, see Time-Varying MPC.

Functions

mpcmoveAdaptiveCompute optimal control with prediction model updating
mpcmoveoptOption set for mpcmove function
mpcstateMPC controller state

Blocks

Adaptive MPC ControllerSimulate adaptive and time-varying model predictive controllers

Topics

Adaptive MPC

Time-Varying MPC

Online Model Updating

  • Model Updating Strategy
    To implement adaptive MPC, you must update the plant model and nominal conditions used by the MPC controller at run time.

Case Studies