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Model Predictive Control Toolbox Functions

Alphabetical List By Category
cloffsetCompute MPC closed-loop DC gain from output disturbances to measured outputs assuming constraints are inactive at steady state
compareCompare two MPC objects
d2dChange MPC controller sample
generateExplicitMPCConvert implicit MPC controller to explicit MPC controller
generateExplicitOptionsOptimization options for explicit MPC generation
generateExplicitRangeBounds on explicit MPC control law parameters
generatePlotParametersParameters for plotSection
getMPC property values
getCodeGenerationDataCreate data structures for mpcmoveCodeGeneration
getconstraintSet custom constraints on linear combinations of plant inputs and outputs
getEstimatorObtain Kalman gains and model for estimator design
getindistRetrieve unmeasured input disturbance model
getnameRetrieve I/O signal names in MPC prediction model
getoutdistRetrieve unmeasured output disturbance model
gpc2mpcGenerate MPC controller using generalized predictive controller (GPC) settings
mpcCreate MPC controller
mpcmoveOptimal control action
mpcmoveAdaptiveCompute optimal control with prediction model updating
mpcmoveCodeGenerationCompute optimal control moves with code generation support
mpcmoveExplicitCompute optimal control using explicit MPC
mpcmoveMultipleCompute gain-scheduling MPC control action at a single time instant
mpcmoveoptOptions set for mpcmove and mpcmoveAdaptive
mpcpropsProvide help on MPC controller properties
mpcqpsolverSolve a quadratic programming problem using the KWIK algorithm
mpcqpsolverOptionsCreate default option set for mpcqpsolver
mpcsimoptMPC simulation options
mpcstateDefine MPC controller state
mpcverbosityChange toolbox verbosity level
plotPlot responses generated by MPC simulations
plotSectionVisualize explicit MPC control law as 2-D sectional plot
reviewExamine MPC controller for design errors and stability problems at run time
sensitivityCompute effect of controller tuning weights on performance
setSet or modify MPC object properties
setconstraintSet custom constraints on linear combinations of plant inputs and outputs
setEstimatorModify a model predictive controller’s state estimator
setindistModify unmeasured input disturbance model
setmpcsignalsSet signal types in MPC plant model
setnameSet I/O signal names in MPC prediction model
setoutdistModify unmeasured output disturbance model
setterminalTerminal weights and constraints
simSimulate closed-loop/open-loop response to arbitrary reference and disturbance signals for implicit or explicit MPC
simplifyReduce explicit MPC controller complexity and memory requirements
sizeSize and order of MPC Controller
ssConvert unconstrained MPC controller to state-space linear system
tfConvert unconstrained MPC controller to linear transfer function
trimCompute steady-state value of MPC controller state for given inputs and outputs
zpkConvert unconstrained MPC controller to zero/pole/gain form
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