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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

`mpcmoveAdaptive`	Compute optimal control with prediction model updating
`mpcmoveopt`	Option set for `mpcmove` function
`mpcstate`	MPC controller state

Blocks

Adaptive MPC Controller

Simulate adaptive and time-varying model predictive controllers

Topics

Adaptive MPC

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.
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.
Adaptive MPC Control of Nonlinear Chemical Reactor Using Linear Parameter-Varying System
Update the internal model of an adaptive MPC controller using an LPV model of the plant dynamics.

Time-Varying MPC

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.
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.
Time-Varying MPC Control of an Inverted Pendulum on a Cart
Control an inverted pendulum in an unstable equilibrium position using a linear time-varying model predictive controller.

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

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 mixed input/output constraints at run time.