Explicit model predictive control uses offline computations to determine all operating regions in which the optimal control moves are determined by evaluating a linear function. Explicit MPC controllers require fewer run-time computations than traditional (implicit) model predictive controllers and are therefore useful for applications that require small sample times. To implement explicit MPC, first design a traditional (implicit) model predictive controller for your application, and then use this controller to generate an explicit MPC controller for use in real-time control. For more information, see Design Workflow for Explicit MPC.
explicitMPC | Explicit model predictive controller |
| Explicit MPC Controller | Explicit model predictive controller |
Explicit model predictive control uses offline computations to determine all operating regions in which the optimal control moves are determined by evaluating a linear function.
Design Workflow for Explicit MPC
To implement explicit MPC, first design a traditional model predictive controller for your application, and then use this controller to generate an explicit MPC controller for use in real-time control.
Explicit MPC Control of a Single-Input-Single-Output Plant
Design and simulate an explicit model predictive controller for a SISO plant.
Explicit MPC Control of an Aircraft with Unstable Poles
Control an unstable aircraft with saturating actuators using an explicit model predictive controller.
Explicit MPC Control of DC Servomotor with Constraint on Unmeasured Output
Design an explicit model predictive controller for a plant with constraints on the manipulated variable and unmeasured output.
Explicit MPC Control of an Inverted Pendulum on a Cart
Control an inverted pendulum in an unstable equilibrium position using an explicit model predictive controller.