Create data structures for
nlmpcmoveCodeGeneration
Use this function to create data structures for the nlmpcmoveCodeGeneration
function, which computes optimal control moves
for nonlinear MPC controllers.
For information on generating data structures for mpcmoveCodeGeneration
, see getCodeGenerationData
.
[
creates data structures for use with coreData
,onlineData
]
= getCodeGenerationData(nlobj
,x
,lastMV
)nlmpcmoveCodeGeneration
.
[
when coreData
,onlineData
]
= getCodeGenerationData(nlobj
,x
,lastMV
,params
)nlobj
is an nlmpc
object then this syntax
copies initial parameter values in the onlineData
structure. If
nlobj
is an nlmpcMultistage
object then
passing the params
argument is not allowed and you have to
manually specify the initial guesses in the InitialGuess
field of
onlineData
instead.
[___] = getCodeGenerationData(___,
enables the specified online weight or constraint field by adding it to the
field
)onlineData
structure.
[___] = getCodeGenerationData(___,field1,...,fieldn)
enables multiple online weight or constraint fields by adding them to the
onlineData
structure.
Create a nonlinear MPC controller with four states, two outputs, and one input.
nlobj = nlmpc(4,2,1);
In standard cost function, zero weights are applied by default to one or more OVs because there are fewer MVs than OVs.
Specify the sample time and horizons of the controller.
Ts = 0.1; nlobj.Ts = Ts; nlobj.PredictionHorizon = 10; nlobj.ControlHorizon = 5;
Specify the state function for the controller, which is in the file pendulumDT0.m
. This discretetime model integrates the continuoustime model defined in pendulumCT0.m
using a multistep forward Euler method.
nlobj.Model.StateFcn = "pendulumDT0";
nlobj.Model.IsContinuousTime = false;
The prediction model uses an optional parameter Ts
to represent the sample time. Specify the number of parameters and create a parameter vector.
nlobj.Model.NumberOfParameters = 1; params = {Ts};
Specify the output function of the model, passing the sample time parameter as an input argument.
nlobj.Model.OutputFcn = "pendulumOutputFcn";
Define standard constraints for the controller.
nlobj.Weights.OutputVariables = [3 3]; nlobj.Weights.ManipulatedVariablesRate = 0.1; nlobj.OV(1).Min = 10; nlobj.OV(1).Max = 10; nlobj.MV.Min = 100; nlobj.MV.Max = 100;
Validate the prediction model functions.
x0 = [0.1;0.2;pi/2;0.3]; u0 = 0.4; validateFcns(nlobj,x0,u0,[],params);
Model.StateFcn is OK. Model.OutputFcn is OK. Analysis of userprovided model, cost, and constraint functions complete.
Only two of the plant states are measurable. Therefore, create an extended Kalman filter for estimating the four plant states. Its state transition function is defined in pendulumStateFcn.m
and its measurement function is defined in pendulumMeasurementFcn.m
.
EKF = extendedKalmanFilter(@pendulumStateFcn,@pendulumMeasurementFcn);
Define initial conditions for the simulation, initialize the extended Kalman filter state, and specify a zero initial manipulated variable value.
x0 = [0;0;pi;0]; y0 = [x0(1);x0(3)]; EKF.State = x0; mv0 = 0;
Create code generation data structures for the controller, specifying the initial conditions and parameters.
[coreData,onlineData] = getCodeGenerationData(nlobj,x0,mv0,params);
View the online data structure.
onlineData
onlineData = struct with fields:
ref: [0 0]
MVTarget: 0
Parameters: {[0.1000]}
X0: [10x4 double]
MV0: [10x1 double]
Slack0: 0
If your application uses online weights or constraints, you must add corresponding fields to the code generation data structures. For example, the following syntax creates data structures that include fields for output variable tuning weights, manipulated variable tuning weights, and manipulated variable bounds.
[coreData2,onlineData2] = getCodeGenerationData(nlobj,x0,mv0,params,... 'OutputWeights','MVWeights','MVMin','MVMax');
View the online data structure. At run time, specify the online weights and constraints in the added structure fields.
onlineData2
onlineData2 = struct with fields:
ref: [0 0]
MVTarget: 0
Parameters: {[0.1000]}
X0: [10x4 double]
MV0: [10x1 double]
Slack0: 0
OutputWeights: [3 3]
MVWeights: 0
MVMin: [10x1 double]
MVMax: [10x1 double]
nlobj
— Nonlinear model predictive controllernlmpc
object  nlmpcMultistage
objectNonlinear model predictive controller, specified as an nlmpc
or nlmpcMultistage
object.
x
— Initial states of nonlinear prediction modelInitial states of the nonlinear prediction model, specified as a column vector of length N_{x}, where N_{x} is the number of prediction model states.
lastMV
— Initial manipulated variable control signalsInitial manipulated variable control signals, specified as a column vector of length N_{mv}, where N_{mv} is the number of manipulated variables.
params
— Initial parameter values for non multistage MPCInitial parameter values for non multistage MPC, specified as a cell
vector with length equal to
nlobj.Model.NumberOfParameters
, which is the number
of optional parameters in the controller prediction model. If the controller
has no optional parameters, specify params
as
{}
.
If nlobj
is an nlmpc
object then the
initial values specified in params
are copied into the
onlineData
structure. If nlobj
is an nlmpcMultistage
object then the
params
argument is not allowed and you have to
manually specify the initial guesses in the InitialGuess
field of onlineData
instead.
For more information on optional prediction model parameters, see Specify Prediction Model for Nonlinear MPC.
field
— Online weight or constraint field nameOnline weight or constraint field name, specified as a string or character
vector. When creating data structures for
nlmpcmoveCodeGeneration
, you can add any of the
following fields to the onlineData
output structure.
Add a given field to the online data structure only if you expect the
corresponding weight or constraint to vary at run time.
Online Constraints
"StateMin"
— State lower bounds
"StateMax"
— State upper bounds
"MVMin"
— Manipulated variable lower
bounds
"MVMax"
— Manipulated variable upper
bounds
"MVRateMin"
— Manipulated variable rate of
change lower bound
"MVRateMax"
— Manipulated variable rate of
change upper bound
Online constraints and Tuning Weights for nonMultistage MPC
"OutputWeights"
— Output variable
weights
"MVWeights"
— Manipulated variable
weights
"MVRateWeights"
— Manipulated variable rate
weights
"ECRWeight"
— Slack variable weight
"OutputMin"
— Output variable lower
bounds
"OutputMax"
— Output variable upper
bounds
Disturbances, Parameters and Initial Guesses for Multistage MPC
"MeasuredDistrubance"
— Measured
disturbances
"StateParameter"
— Parameter vector for state
function and Jacobians
"StageParameter"
— Parameter vector for stage
cost, constraints and Jacobians
"TerminalState"
— Terminal State
constraint
"InitialGuess"
— Initial guesses for decision
variables
coreData
— Nonlinear MPC configuration parametersNonlinear MPC configuration parameters that are constant at run time,
returned as a structure. These parameters are derived from the controller
settings in nlobj
. When simulating your controller,
pass coreData
to nlmpcmoveCodeGeneration
without changing any
parameters.
onlineData
— Online nonlinear MPC controller dataRuntime simulation data, specified as structure with the following fields.
NonMultistage MPC
— Structure for generic MPC controllersOnline nonlinear MPC controller data that you must update at each control interval, returned as a structure. The structure always contains the following fields.
Field  Description 

ref  Output reference values, returned as a
column vector of zeros with length

mvTarget  Manipulated variable reference values, returned as a column vector of zeros with length N_{mv}, where N_{mv} is the number of manipulated variables. 
X0  Initial guess for the state trajectory,
returned as a column vector equal to

MV0  Initial guess for the manipulated
variable trajectory, returned as a column vector
equal to

Slack0  Initial guess for the slack variable, returned as zero. 
onlineData
can also contain the following
fields, depending on the controller configuration and argument
values.
Field  Description 

md  Measured disturbance values — This
field is returned only when the controller has
measured disturbance inputs, that is, when

Parameters  Parameter values — This field is
returned only when the controller uses optional
model parameters. 
 Weight and constraint values — Each field is
returned only when the corresponding field name is
specified using the field
argument. The value of each field is equal to the
corresponding default value defined in the
controller, as returned in
coreData . 
For more information on configuring
onlineData
fields, see nlmpcmoveCodeGeneration
.
Multistage MPC
— Structure for multistage MPC controllersOnline nonlinear multistage MPC controller data that you must
update at each control interval, returned as a structure. The
structure always contains the InitialGuess
field.
Field  Description 

InitialGuess  Initial guess for the decision
variables returned as a column vector of length
equal to the sum of the lengths of all the
decision variable vectors for each stage. For more
information, see 
onlineData
can also contain the following
fields, depending on the controller configuration and argument
values.
Field  Description 

MeasuredDisturbances  Measured disturbance values — This
field is returned only when the controller has
measured disturbance inputs, that is, when

StateFcnParameters  Parameter values for state functions
and Jacobians — This field is returned only when
the controller state prediction function or its
Jacobian use model parameters, that is when

StageFcnParameters  Parameter values for stage cost and
constraints functions and their Jacobians— This
field is returned only when any stage cost or
constraint function, or its Jacobian, uses
parameters, that is when there is at least one
stage 
 Constraint values — Each field is returned
only when the corresponding field name is
specified using the field
argument. The value of each field is equal to the
corresponding default value defined in the
controller, as returned in
coreData . 
TerminalState  Terminal state, specified as a column
vector with as many elements as the number of
states. The terminal state is the desired state at
the last prediction step. To specify desired
terminal states at runtime via this field, you
must specify finite values in the

For more information on configuring
onlineData
fields, see nlmpcmove
and nlmpcmoveCodeGeneration
.
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