# getCodeGenerationData

Create data structures for `mpcmoveCodeGeneration`

## Syntax

## Description

Use this function to create data structures for the `mpcmoveCodeGeneration`

function, which computes optimal control moves for
implicit and explicit linear MPC controllers.

For information on generating data structures for `nlmpcmoveCodeGeneration`

, see `getCodeGenerationData`

.

`[`

creates data structures for use with `configData`

,`stateData`

,`onlineData`

]
= getCodeGenerationData(`mpcobj`

)`mpcmoveCodeGeneration`

.

`[___] = getCodeGenerationData(___,`

specifies additional options using one or more `Name,Value`

)`Name,Value`

pair
arguments.

## Examples

### Create MPC Code Generation Data Structures

Create a plant model, and define the MPC signal types.

plant = rss(3,2,2); plant.D = 0; plant = setmpcsignals(plant,'mv',1,'ud',2,'mo',1,'uo',2);

Create an MPC controller.

mpcObj = mpc(plant,0.1);

-->"PredictionHorizon" is empty. Assuming default 10. -->"ControlHorizon" is empty. Assuming default 2. -->"Weights.ManipulatedVariables" is empty. Assuming default 0.00000. -->"Weights.ManipulatedVariablesRate" is empty. Assuming default 0.10000. -->"Weights.OutputVariables" is empty. Assuming default 1.00000. for output(s) y1 and zero weight for output(s) y2

Configure your controller parameters. For example, define bounds for the manipulated variable.

mpcObj.ManipulatedVariables.Min = -1; mpcObj.ManipulatedVariables.Max = 1;

Create code generation data structures.

[configData,stateData,onlineData] = getCodeGenerationData(mpcObj);

-->Converting model to discrete time. -->The "Model.Disturbance" property is empty: Assuming unmeasured input disturbance #2 is integrated white noise. Assuming no disturbance added to measured output #1. -->"Model.Noise" is empty. Assuming white noise on each measured output. -->Converting model to discrete time. -->The "Model.Disturbance" property is empty: Assuming unmeasured input disturbance #2 is integrated white noise. Assuming no disturbance added to measured output #1. -->"Model.Noise" is empty. Assuming white noise on each measured output.

### Specify Options for Creating MPC Code Generation Structures

Create a plant model, and define the MPC signal types.

plant = rss(3,2,2); plant.D = 0;

Create an MPC controller.

mpcobj = mpc(plant,0.1);

-->"PredictionHorizon" is empty. Assuming default 10. -->"ControlHorizon" is empty. Assuming default 2. -->"Weights.ManipulatedVariables" is empty. Assuming default 0.00000. -->"Weights.ManipulatedVariablesRate" is empty. Assuming default 0.10000. -->"Weights.OutputVariables" is empty. Assuming default 1.00000.

Create code generation data structures. Configure options to:

Use single-precision floating-point values in the generated code.

Improve computational efficiency by not computing optimal sequence data.

Run your MPC controller in adaptive mode.

[configData,stateData,onlineData] = getCodeGenerationData(mpcobj,... 'DataType','single',OnlyComputeCost=true,IsAdaptive=true);

-->Converting model to discrete time. -->Assuming output disturbance added to measured output #1 is integrated white noise. -->Assuming output disturbance added to measured output #2 is integrated white noise. -->"Model.Noise" is empty. Assuming white noise on each measured output. -->Converting model to discrete time. -->Assuming output disturbance added to measured output #1 is integrated white noise. -->Assuming output disturbance added to measured output #2 is integrated white noise. -->"Model.Noise" is empty. Assuming white noise on each measured output.

## Input Arguments

`mpcobj`

— Model predictive controller

`mpc`

object | `explicitMPC`

object

Model predictive controller, specified as one of the following:

`mpc`

object — MPC controller`explicitMPC`

object — Explicit MPC controller created using`generateExplicitMPC`

.

### Name-Value Arguments

Specify optional pairs of arguments as
`Name1=Value1,...,NameN=ValueN`

, where `Name`

is
the argument name and `Value`

is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.

*
Before R2021a, use commas to separate each name and value, and enclose*
`Name`

*in quotes.*

**Example: **`'DataType','single'`

specifies that the generated code
uses single-precision floating point values.

`DataType`

— Data type used in generated code

`'double'`

(default) | `'single'`

Data type used in generated code when using
`mpcmoveCodeGeneration`

, specified as specified
as the comma-separated pair consisting of `'DataType'`

and one of the following:

`'double'`

— Use double-precision floating point values.`'single'`

— Use single-precision floating point values.

`OnlyComputeCost`

— Toggle for computing only optimal cost

`false`

(default) | `true`

Toggle for computing only optimal cost during simulation when using
`mpcmoveCodeGeneration`

, specified as specified
as the comma-separated pair consisting of
`'OnlyComputeCost'`

and either
`true`

or `false`

. To reduce
computational load by not calculating optimal sequence data, set
`OnlyComputeCost`

to
`true`

.

`IsAdaptive`

— Adaptive MPC indicator

`false`

(default) | `true`

Adaptive MPC indicator when using
`mpcmoveCodeGeneration`

, specified as specified
as the comma-separated pair consisting of
`'IsAdaptive'`

and either `true`

or `false`

. Set `IsAdaptive`

to
`true`

if your controller is running in adaptive
mode.

For more information on adaptive MPC, see Adaptive MPC.

**Note**

`IsAdaptive`

and `IsLTV`

cannot
be `true`

at the same time.

`IsLTV`

— Time-varying MPC indicator

`false`

(default) | `true`

Time-varying MPC indicator when using
`mpcmoveCodeGeneration`

, specified as the
comma-separated pair consisting of `'IsLTV'`

and either
`true`

or `false`

. Set
`IsLTV`

to `true`

if your
controller is running in time-varying mode.

For more information on time-varying MPC, see Time-Varying MPC.

**Note**

`IsAdaptive`

and `IsLTV`

cannot
be `true`

at the same time.

`UseVariableHorizon`

— Variable horizon indicator

`false`

(default) | `true`

Variable horizon indicator when using
`mpcmoveCodeGeneration`

, specified as the
comma-separated pair consisting of
`'UseVariableHorizon'`

and either
`true`

or `false`

. To vary your
prediction and control horizons at run time, set
`UseVariableHorizons`

to
`true`

.

When you use variable horizons,
`mpcmoveCodeGeneration`

ignores the horizons
specified in `configData`

and instead uses the
prediction and control horizon specified in
`onlineData.horizons`

.

For more information, see Adjust Horizons at Run Time.

## Output Arguments

`configData`

— MPC configuration parameters

structure

MPC configuration parameters that are constant at run time, returned as a
structure. These parameters are derived from the controller settings in
`mpcobj`

. When simulating your controller, pass
`configData`

to `mpcmoveCodeGeneration`

without
changing any parameters.

For more information on how generated MPC code uses constant matrices in
`configData`

to solve the QP problem, see QP Problem Construction for Generated C Code.

`stateData`

— Initial controller states

structure

Initial controller states, returned as a structure. To initialize your
simulation with the initial states defined in `mpcobj`

,
pass `stateData`

to `mpcmoveCodeGeneration`

. To use
different initial conditions, modify `stateData`

. You can
specify nondefault controller states using
`InitialState`

.

For more information on the `stateData`

fields, see
`mpcmoveCodeGeneration`

.

`stateData`

has the following fields.

Field | Description |
---|---|

`Plant` | Plant model state estimates |

`Disturbance` | Unmeasured disturbance model state estimates |

`Noise` | Output measurement noise model state estimates |

`LastMove` | Manipulated variable control moves from previous control interval |

`Covariance` | Covariance matrix for controller state estimates |

`iA` | Active inequality constraints |

`onlineData`

— Online MPC controller data

structure

Online MPC controller data that you must update at each control interval, returned as a structure with the following fields.

Field | Description | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|

`signals` | Input and output signals, returned as a structure with the following fields.
| ||||||||||||

`limits` | Input and output constraints, returned as a structure with the following fields:
When | ||||||||||||

`weights` | Updated QP optimization weights, returned as a structure with the following fields:
When | ||||||||||||

`customconstraints` | Updated custom mixed input/output constraints, returned as a structure with the following fields:
When | ||||||||||||

`horizons` | Updated controller horizon values, returned as a structure with the following fields:
The When
| ||||||||||||

`model` | Updated plant and nominal values for adaptive MPC and time-varying MPC, returned as a structure with the following fields:
The |

`getCodeGenerationData`

returns
`onlineData`

with empty matrices for all structure
fields, except `signals.ref`

,
`signals.ym`

, and `signals.md`

. These
fields contain the corresponding nominal signal values from
`mpcobj`

. If your controller does not have measured
disturbances, `signals.md`

is returned as an empty
matrix.

For more information on configuring `onlineData`

fields, see `mpcmoveCodeGeneration`

.

## Version History

**Introduced in R2016a**

## MATLAB 명령

다음 MATLAB 명령에 해당하는 링크를 클릭했습니다.

명령을 실행하려면 MATLAB 명령 창에 입력하십시오. 웹 브라우저는 MATLAB 명령을 지원하지 않습니다.

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