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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
mpcmoveoptOptions set for mpcmove and mpcmoveAdaptive
mpcstateDefine MPC controller state

Blocks

Adaptive MPC ControllerDesign and simulate adaptive and time-varying model predictive controllers

Topics

Getting Started

Adaptive MPC

To control strongly nonlinear or time-varying systems, you can use adaptive MPC to update the controller internal model for changing operating conditions.

Time-Varying MPC

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.

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.

Adaptive MPC Control of Nonlinear Chemical Reactor Using Successive Linearization

Update the internal model of an adaptive MPC controller by linearizing the nonlinear plant at each control interval.

Adaptive MPC Control of Nonlinear Chemical Reactor Using Online Model Estimation

Update the internal model of an adaptive MPC controller by estimating a plant model at each control interval.

Time-Varying MPC Control of a Time-Varying Plant

Achieve better performance when controlling a time-varying plant by using a prediction model and nominal conditions that vary over the prediction horizon.

Case Studies

Obstacle Avoidance Using Adaptive Model Predictive Control

Use adaptive MPC to make a vehicle follow a reference velocity and avoid obstacles by updating the plant model and linear custom constraints at run time.

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