mpcprops

 MPC controller properties (with Ny output variables
     Nu manipulated variables, a prediction horizon of p intervals,
     and control horizon of m intervals):

 Model - 
 A structure consisting of plant,
 disturbance and noise models and their nominal values.
     Model.Plant -
     Plant model
         (LTI or linear model from System Identification Toolbox).
         Default: none, must be specified.

     Model.Disturbance -
         Model describing unmeasured input disturbances. Must be
         an LTI or linear model from System Identification Toolbox.
         Default: integrator (models step disturbance).
         See also: "getindist" and "setindist" commands.
     Model.Noise -
         Model describing added output measurement noise. Must be
         an LTI or linear model from System Identification Toolbox.
         Default: unity gain (models white noise).
     Model.Nominal -
         Structure containing nominal state, input,
         and output variable values:
         Model.Nominal.X -
             State of Model.Plant at the operating point.
         Model.Nominal.U -
             Input of Model.Plant at the operating point.
         Model.Nominal.Y -
             Output of Model.Plant at the operating point.
         Model.Nominal.DX -
             State derivative (for continuous time models) or update
             (for discrete time models) at the operating point.
         Default: all nominal values set to zero.
     
    Define input signal types in Model.Plant.InputGroup:
        ManipulatedVariables (or MV or Manipulated or Input) -
            Indices of manipulated variables.
        UnmeasuredDisturbances (or UD or Unmeasured) -
            Indices of unmeasured disturbances.
        MeasuredDisturbances (or MD or Measured) -
            Indices of measured disturbances.
    By default, all the plant inputs are manipulated variables.
    See also:  the "setmpcsignals" command.
    
    Define output signal types in Model.Plant.OutputGroup:
        MeasuredOutputs (or MO or Measured) -
            Indices of measured outputs.
        UnmeasuredOutputs (or UO or Unmeasured) -
            Indices of unmeasured outputs.
    By default, all the plant outputs are measured outputs.
    See also:  the "setmpcsignals" command.
    
 Ts - 
    Sample time of the MPC controller
    (in the same time units as Model.Plant).
    Default: if Model.Plant.Ts > 0, MPC.Ts = Model.Plant.Ts;
             otherwise, MPC.Ts must be specified.

 PredictionHorizon - 
     Intervals in the prediction horizon (scalar)
     Default: 10 + max intervals of delay in Model.Plant

 ControlHorizon - 
     Intervals in the control horizon.
     Either a scalar or a vector of blocked moves.
     Default: 2

 Weights - 
     A structure defining dimensionless
     MPC weights with the following fields:
     Weights.ManipulatedVariables
         (or MV or Manipulated or Input) -
         Must be a (min 1, max p) x Nu matrix of weights
         on the manipulated variables.
         Default: zeros(1,Nu)
     Weights.ManipulatedVariablesRate
         (or MVRate or ManipulatedRate or InputRate) -
         Must be a (min 1, max p) x Nu matrix of weights on the rates
         of the manipulated variables. MV Rates are defined as the
         differences between current and ptrevious MV values.
         Default: 0.1*ones(1,Nu)
     Weights.OutputVariables (or OV or Output) -
         Must be a (min 1, max p) x Ny matrix of weights
         on the plant outputs.
         Default: if Ny<=Nu, ones(1,Ny); otherwise,
                  only Nu outputs are weighted,
                  with preference on measured outputs.
     Weights.ECR - Scalar weight on the slack variable
         Equal Concern for Relaxation, used for constraint softening.
         Default: 1e5*max(Weights)

     Alternative weighting:
     This syntax allows for off-diagonal weights, but requires the
     weights to be identical at each prediction horizon step.
     Using this syntax, Weights.MV={R}, where R is a Nu x Nu
     symmetric and positive semi-definite matrix,
     which must be constant over the prediction horizon.
     The syntax for Weights.MVRate and Weights.OV is similar.

 ManipulatedVariables (or MV or Manipulated or Input) - 
     Array of structures with fields:
     MV(i).Min -
         1 to p dimensional vector of lower bounds on MV #i
         Ddefault: -Inf
          .Max -
         1 to P dimensional vector of upper bounds on MV #i
         Default:  Inf
          .MinECR -
         1 to p dimensional vector of weights for softening the
         lower bounds on MV #i
         Default: 0, (hard constraint).
          .MaxECR -
         1 to p dimensional vector of weights for softening the
         upper bounds on MV #i
         Default: 0, (hard constraint).
          .RateMin -
         1 to p dimensional vector of lower bounds on the rate of MV #i
         Default: -Inf
          .RateMax -
         1 to p dimensional vector of upper bounds on the rate of MV #i
         Default: Inf
          .MinECR -
         1 to p dimensional vector of weights for softening the
         lower bounds on the MV #i rate
         Default: 0, (hard constraint).
          .MaxECR -
         1 to p dimensional vector of weights for softening the
         upper bounds on the MV #i rate
         Default: 0, (hard constraint).
          .Target -
         1 to p dimensional vector of target values for MV #i
         Default: Model.Nominal.U
          .Name -
         Name of MV #i
         Default: from Model.Plant.InputName
          .Units -
         String specifying the engineering units for MV #i
          .ScaleFactor -
         A scalar in engineering units.
         Each MV will be divided by its scale factor to form the
         dimensionless signal used in the MPC computations.
         Default: 1
           .Type -
         Type of variable MV #i (default: 'continuous').
         Type can be 'continuous', 'binary', 'integer',
         or an array containing all the values MV #i can take.

 OutputVariables (or OV or Controlled or Output) - 
         Array of structures with fields:
     OV(i).Min -
         1 to p dimensional vector of lower bounds on OV #i.
         Default: -Inf
          .Max -
         1 to p dimensional vector of upper bounds on OV #i.
         Default:  Inf
          .MinECR -
         1 to p dimensional vector of weights for softening the
         lower bounds on OV #i.
         Default: 1, (soft constraint).
          .MaxECR -
         1 to p dimensional vector of weights for softening the
         upper bounds on OV #i.
         Default: 1, (soft constraint).
          .Name -
         Name of OV #i (default: Model.Plant.OutputName{i})
          .Units -
         String specifying the engineering units for OV #i
          .ScaleFactor -
         A scalar in engineering units.
         Each OV will be divided by its scale factor to form the
         dimensionless signal used in the MPC computations.
         Default: 1

 DisturbanceVariables (or DV or Disturbance) - 
     Array of structures with fields:
     DV(i).Name -
         Name of DV #i (default: from Model.Plant.InputName).
          .Units -
         String specifying the engineering units for DV #i
          .ScaleFactor -
         A scalar in engineering units.
         Each DV will be divided by its scale factor to form the
         dimensionless signal used in all the MPC computations.
         Default: 1
     Note: DV consists in all the measured disturbance inputs
           followed by all the unmeasured disturbance inputs.

 Optimizer - 
     QP optimizer parameter structure with fields:
     Optimizer.Algorithm -
         Algorithm used by the solver.
         Default: 'active-set'
     Optimizer.ActiveSetOptions -
         Active-set solver options.
     Optimizer.InteriorPointOptions -
         Interior-point solver options.
     Optimizer.MixedIntegerOptions -
         Mixed-integer solver options.
     Optimizer.MinOutputECR -
         Minimum value of output MinECR and MaxECR.
         Default: 0
     Optimizer.UseSuboptimalSolution -
         If True the controller applies the sub-optimal solution
         when the maximum number of iterations is exceeded.
         Default: false.
     Optimizer.CustomSolver -
         If true the custom QP solver is used for simulation.
         Default: false.
     Optimizer.CustomSolverCodeGen -
         If true the custom QP solver is used for code generation.
         Default: false.

 Notes - User's notes.
     It can be a string or a cell array of strings.                 
                 
 UserData - Additional information or data.
     It can be any MATLAB data type.
                 
 History - Date and time of the MPC object creation.

 See the "mpc" command for construction syntax.