Gain-Scheduled MPC Design

Gain-scheduled control of nonlinear plants by switching controllers at run time

Gain-scheduled model predictive control switches between a predefined set of MPC controllers, in a coordinated fashion, to control a nonlinear plant over a wide range of operating conditions. Use this approach if a single prediction model cannot provide adequate controller performance. To implement gain-scheduled MPC, first design a model predictive controller for each operating point, and then design a scheduling signal that switches the controllers at run time. To reduce online computational effort, you can also implement gain-scheduled explicit MPC in Simulink®. For more information, see Gain-Scheduled MPC.


mpcmoveMultipleCompute gain-scheduling MPC control action at a single time instant
mpcmoveoptOption set for mpcmove function
mpcstateMPC controller state


Multiple MPC ControllersSimulate switching between multiple implicit MPC controllers
Multiple Explicit MPC ControllersMultiple explicit MPC controllers


Gain-Scheduled MPC Basics

Gain-Scheduled MPC

Control a nonlinear plant over a wide range of operating conditions by switching between a predefined set of MPC controllers in a coordinated fashion.

Schedule Controllers at Multiple Operating Points

Control a nonlinear system by designing multiple MPC controllers for different plant operating conditions.

Case Studies

Gain-Scheduled MPC Control of Nonlinear Chemical Reactor

Control a nonlinear chemical reactor using a gain-scheduled model predictive controller as the reactor transitions from one operating condition to another.

Gain-Scheduled Implicit and Explicit MPC Control of Mass-Spring System

Implement gain-scheduled MPC control of a nonlinear plant using the Multiple MPC Controllers block and Multiple Explicit MPC Controllers block.

Gain-Scheduled MPC Control of an Inverted Pendulum on a Cart

Control an inverted pendulum in an unstable equilibrium position using a gain-scheduled model predictive controller.