Model Predictive Control Toolbox Functions

cloffset Compute MPC closed-loop DC gain from output disturbances to measured outputs assuming constraints are inactive at steady state
compare Compare two MPC objects
d2d Change MPC controller's sampling time
generateExplicitMPC Convert implicit MPC controller to explicit MPC controller
generateExplicitOptions Optimization options for explicit MPC generation
generateExplicitRange Bounds on explicit MPC control law parameters
generatePlotParameters Parameters for plotSection
get MPC property values
getconstraint Model Predictive Control custom constraint definitions
getEstimator Obtain Kalman gains and model for estimator design
getindist Unmeasured input disturbance model
getname I/O signal names in MPC prediction model
getoutdist Unmeasured output disturbance model
gpc2mpc Generate MPC controller using generalized predictive controller (GPC) settings
mpc Create MPC controller
mpcmove Optimal control action
mpcmoveAdaptive Compute optimal control with prediction model updating
mpcmoveExplicit Compute optimal control using explicit MPC
mpcmoveMultiple Compute gain-scheduling MPC control action at a single time instant
mpcmoveopt Options set for mpcmove and mpcmoveAdaptive
mpcprops Provide help on MPC controller's properties
mpcsimopt MPC simulation options
mpcstate Define MPC controller state
mpctool Start Model Predictive Controller GUI
mpcverbosity Change toolbox verbosity level
plot Plot responses generated by MPC simulations
plotSection Visualize explicit MPC control law as 2-D sectional plot
review Examine MPC controller for design errors and stability problems at run-time
sensitivity Compute effect of controller tuning weights on performance
set Set or modify MPC object properties
setconstraint Custom constraints on plant inputs and outputs
setEstimator Modify a model predictive controller's state estimator
setindist Modify unmeasured input disturbance model
setmpcsignals Set signal types in MPC plant model
setname Set I/O signal names in MPC prediction model
setoutdist Modify unmeasured output disturbance model
setterminal Terminal weights and constraints
sim Simulate closed-loop/open-loop response to arbitrary reference and disturbance signals for implicit or explicit MPC
simplify Reduce explicit MPC controller complexity and memory requirements
size Size and order of MPC Controller
ss Convert unconstrained MPC controller to state-space linear system
tf Convert unconstrained MPC controller to linear transfer function
trim Compute steady-state value of MPC controller state for given inputs and outputs
zpk Convert unconstrained MPC controller to zero/pole/gain form
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