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Explicit MPC Design

Fast model predictive control using precomputed solutions instead of run-time optimization

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.

Functions

generateExplicitMPCConvert implicit MPC controller to explicit MPC controller
generateExplicitRangeBounds on explicit MPC control law parameters
generateExplicitOptionsOptimization options for explicit MPC generation
simplifyReduce explicit MPC controller complexity and memory requirements
plotSectionVisualize explicit MPC control law as 2-D sectional plot
generatePlotParametersParameters for plotSection
mpcmoveExplicitCompute optimal control using explicit MPC
mpcmoveoptOptions set for mpcmove and mpcmoveAdaptive
mpcstateDefine MPC controller state
simSimulate closed-loop/open-loop response to arbitrary reference and disturbance signals for implicit or explicit MPC
mpcsimoptMPC simulation options

Blocks

Explicit MPC ControllerDesign and simulate explicit model predictive controller

Topics

Getting Started

Explicit MPC

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.

Case Studies

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.

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