MPT3 Wiki | UI / Codegen

December 20, 2013, at 09:01 AM by 129.132.29.86 -

Changed line 138 from:

The first argument represents the PWA/PWQ function to export, the second argument is the base name for the files to be generated and the third argument is the tie-breaking function to deal with multiple valued ~~function~~. The generated mex-file can be compiled:

to:

The first argument represents the PWA/PWQ function to export, the second argument is the base name for the files to be generated and the third argument is the tie-breaking function to deal with multiple valued cases. The generated mex-file can be compiled:

December 19, 2013, at 03:50 PM by 129.132.29.86 -

Changed lines 131-136 from:

From version 3.0.14 we have introduced @@toC@@ methods that export general PWA/PWQ functions to C language.

!!! Export using Matlab Coder toolbox
One straightforward way to obtain a C-code representation of parametric solutions is to use the Matlab Coder toolbox:

to:

From version 3.0.14 we have introduced @@toC()@@ methods that export general PWA/PWQ functions to C language. The basic sequential search (including tie-breaking) is exported using the @@toC()@@ method operating over @@PolyUnion@@ object. The binary search trees are exported in @@BinTreePolyUnion/toC()@@ method. The syntax for code generation applied for the example above is given as

(:source lang=MATLAB :) [@
ctrl.optimizer.toC('primal','file','obj')
Output written to "file.c".
C-mex function written to "file_mex.c".
@]
The first argument represents the PWA/PWQ function to export, the second argument is the base name for the files to be generated and the third argument is the tie-breaking function to deal with multiple valued function. The generated mex-file can be compiled:
(:source lang=MATLAB :) [@
mex file_mex.c
@]
and evaluated inside Matlab
(:source lang=MATLAB :) [@
file_mex(x0)

ans =

-1
-1
-0.76229508196722
-0.0737704918032785
1.32093882317646e-15
@]
The result gives the same output as evaluating the Matlab file @@mycontroller@@ in the above example.

December 19, 2013, at 03:31 PM by 129.132.29.86 -

Changed lines 90-92 from:

~~One straightforward way to obtain a C-code representation of parametric solutions is to use the Matlab Coder toolbox:~~

to:

!!! Export of PWA control law stored in @@EMPCController@@ object
The @@EMPCController@@ object contains a method @@exportToC@@ that exports PWA control law stored in the @@optimizer@@ property to C language. The syntax of @@exportToC@@ method is given as
(:source lang=MATLAB :) [@
ctrl.exportToC('output','directory')
@]
where @@output@@ is the base name for the C-files to be generated in @@directory@@. In the new @@directory@@ there will be three files located:
* @@output.c@@ - pure C-code with PWA control law
* @@output_mex.c@@ - mex interface for fast evaluation in Matlab
* @@output_sfunc.c@@ - Simulink interface for fast evaluation in Simulink
The @@output.c@@ contains the pure C-code that can be ported to target application. For fast evaluation in Matlab (Simulink), one may be interested to compile the mex (Simulink) interfaces by issuing the command
(:source lang=MATLAB :) [@
mex output_mex.c
mex output_sfunc.c
@]
The compiled files can be called from Matlab (Simulink) as any other function. For the above example, the compiled function @@output_mex@@ evaluates to the same output as the generated Matlab files

(:source lang=MATLAB :) [@
% output from the compiled C-mex function
output_mex(x0)

ans =

-1
-1
-0.76229508196722
-0.0737704918032785
1.32093882317646e-15

% output from the generated matlab file
mycontroller(x0)

ans =

-1
-1
-0.76229508196722
-0.0737704918032785
1.32093882317646e-15
@]

!!! Export of general PWA/PWQ functions
From version 3.0.14 we have introduced @@toC@@ methods that export general PWA/PWQ functions to C language.

!!! Export using Matlab Coder toolbox

December 19, 2013, at 02:38 PM by 129.132.29.86 -

Deleted lines 6-13:

!! Important note

This feature is currently only available in development releases of MPT3. To install the latest development version, run the following:
(:source lang=MATLAB :) [@
tbxmanager source add http://www.tbxmanager.com/package/unstable.xml/mpt
tbxmanager update
@]

November 06, 2013, at 12:00 PM by mk -

Changed lines 4-5 from:

# [[#Matlab-export|Export to pure Matlab code]]

to:

# [[#Matlab-export|Export of generic parametric solutions to pure Matlab code]]
# [[#Tree-export|Export of binary trees to pure Matlab code]]

Added line 76:

[[#Tree-export]]

November 06, 2013, at 11:59 AM by mk -

Added lines 73-91:

@]

!! Export of binary trees to pure Matlab code

The @@BinTreePolyUnion/toMatlab@@ method exports a given binary tree to a pure Matlab code, similarly to the procedure above. Note that the method has following limitations:
* supports only a single @@BinTreePolyUnion@@ object
* no tiebreaking

Example:
(:source lang=MATLAB :) [@
% construct the binary tree
tree = BinTreePolyUnion(ctrl.optimizer);

% export the tree solution to a standalone m-file
tree.toMatlab('mycontroller.m', 'primal');

% evaluate the exported solution for a particular state
x0 = [2; 1];
[U, region] = mycontroller(x0)

November 01, 2013, at 07:11 PM by mk -

Changed lines 4-6 from:

# Export to pure Matlab code
# Export to C code

to:

# [[#Matlab-export|Export to pure Matlab code]]
# [[#C-export|Export to C code]]

Added line 15:

[[#Matlab-export]]

Changed lines 36-37 from:

This tells MPT to export the primal optimizer (stored as the @@primal@@ function of the @@optimizer@@ field of the controller), resolving tiebreaks using the cost function of the controller (stored as the @@obj@@ function of @@controller.optimizer).

to:

This tells MPT to export the primal optimizer (stored as the @@primal@@ function of the @@optimizer@@ field of the controller), resolving tiebreaks using the cost function of the controller (stored as the @@obj@@ function of @@controller.optimizer@@).

Added line 75:

[[#C-export]]

November 01, 2013, at 09:24 AM by mk -

Changed lines 64-65 from:

[U, region] = mycontroller(x0);

to:

[U, region] = mycontroller(x0)
if region==0
error('No region for state %s.', mat2str(x0));
end

Changed line 71 from:

uopt = U(1:nu);

to:

uopt = U(1:nu)

November 01, 2013, at 09:22 AM by mk -

Added lines 65-68:

% note that U contains the open-loop optimizer. to get the closed-loop control action, use
nu = 1; % number of control inputs
uopt = U(1:nu);

November 01, 2013, at 09:16 AM by mk -

Changed line 42 from:

Here, @@trimFunction('primal', nu)@@ will change the @@primal@@ function such that it only returns the closed-loop optimizer (i.e., the first @@nu@@ components of the open-loop optimizer).

to:

Here, @@trimFunction('primal', nu)@@ will change the @@primal@@ function such that it only returns the closed-loop optimizer (i.e., the first @@nu@@ components of the open-loop optimizer). The added benefit is in decreased memory consumption.

November 01, 2013, at 09:15 AM by mk -

Changed line 17 from:

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method. The exported code is completely MPT-independent and, more importantly, much faster to execute compared to built-in MPT function-evaluation code (which needs to perform lots of sanity checks which slow down the evaluation process).

to:

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method (see @@help PolyUnion/toMatlab@@ for more information). The exported code is completely MPT-independent and, more importantly, much faster to execute compared to built-in MPT function-evaluation code (which needs to perform lots of sanity checks which slow down the evaluation process).

November 01, 2013, at 09:13 AM by mk -

Changed line 37 from:

Note that, by default, the @@toMatlab@@ method exports the full open-loop optimizer. In the case of explicit MPC this implies that the output of @@z=name_of_file(x)@@ will be an {$ N ~~\times~~ n_u $} vector, where {$ N $} is the prediction horizon and {$ n_u $} is the number of control inputs. Then the closed-loop control action is given by @@u = z(1:nu)@@. Alternatively, you can ask @@toMatlab()@@ to only export the closed-loop optimizer. This can be achieved by:

to:

Note that, by default, the @@toMatlab@@ method exports the full open-loop optimizer. In the case of explicit MPC this implies that the output of @@z=name_of_file(x)@@ will be an {$ N n_u \times 1$} vector, where {$ N $} is the prediction horizon and {$ n_u $} is the number of control inputs. Then the closed-loop control action is given by @@u = z(1:nu)@@. Alternatively, you can ask @@toMatlab()@@ to only export the closed-loop optimizer. This can be achieved by:

November 01, 2013, at 09:12 AM by mk -

Changed lines 72-73 from:

~~solution~~.toMatlab('~~name_of_file~~.m', 'primal', 'obj');
coder ~~name_of_file~~ -args {zeros(nx, 1)}

to:

controller.optimizer.toMatlab('mycontroller.m', 'primal', 'obj');
coder mycontroller -args {zeros(nx, 1)}

Changed line 75 from:

where @@nx@@ is the number of parameters. The @@coder@@ function will generate the mex-function @@~~name~~_~~of_file_~~mex()@@ which is much faster to execute compared to executing @@~~name_of_file~~.m@@.

to:

where @@nx@@ is the number of parameters. The @@coder@@ function will generate the mex-function @@controller_mex()@@ which is much faster to execute compared to executing @@controller.m@@.

November 01, 2013, at 09:11 AM by mk -

Added lines 76-77:

For explicit MPC controllers you can obtain @@nx@@ by @@nx=controller.xinitFormat.n_xinit@@ (this number already includes any additional parameters introduced by free reference tracking and/or by the {$ \Delta u $} formulation).

November 01, 2013, at 09:09 AM by mk -

Changed lines 17-18 from:

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method. The exported ~~file~~ is completely MPT-independent and, more importantly, much faster to ~~evaluate~~ compared to built-in MPT evaluation code (which needs to perform lots of sanity checks which slow down the evaluation process).

to:

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method. The exported code is completely MPT-independent and, more importantly, much faster to execute compared to built-in MPT function-evaluation code (which needs to perform lots of sanity checks which slow down the evaluation process).

Added lines 68-75:

One straightforward way to obtain a C-code representation of parametric solutions is to use the Matlab Coder toolbox:

(:source lang=MATLAB :) [@
solution.toMatlab('name_of_file.m', 'primal', 'obj');
coder name_of_file -args {zeros(nx, 1)}
@]
where @@nx@@ is the number of parameters. The @@coder@@ function will generate the mex-function @@name_of_file_mex()@@ which is much faster to execute compared to executing @@name_of_file.m@@.

November 01, 2013, at 09:05 AM by mk -

Changed lines 17-19 from:

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method. ~~Example~~:

to:

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method. The exported file is completely MPT-independent and, more importantly, much faster to evaluate compared to built-in MPT evaluation code (which needs to perform lots of sanity checks which slow down the evaluation process).

The general syntax is as follows:

Added lines 21-45:

solution.toMatlab('name_of_file.m', 'function_to_export', 'tiebreak_function')
@]
The method takes any @@PolyUnion@@ object (or an array thereof) and exports the function @@function_to_export@@ to file @@name_of_file@@, resolving tiebreak (when a particular point is contained in multiple regions) using the function @@tiebreak_function@@. If you have a single optimizer that is continuous, you can use set @@tiebreak_function='first-region'@@. Here, the search for a region that contains a particular point is finished upon hitting the first such region.

The exported parametric solution can then be evaluated by
(:source lang=MATLAB :) [@
[z, region] = name_of_file(x)
@]
where @@x@@ is the vector of parameters at which to evaluate, @@z@@ is the value of the optimizer at @@x@@, and @@region@@ is the index of the region that constains @@x@@. If there is no region containing @@x@@, then @@z=NaN@@ and @@region=0@@.

To export explicit MPC feedbacks, use the following syntax:
(:source lang=MATLAB :) [@
controller.optimizer.toMatlab('name_of_file.m', 'primal', 'obj')
@]
This tells MPT to export the primal optimizer (stored as the @@primal@@ function of the @@optimizer@@ field of the controller), resolving tiebreaks using the cost function of the controller (stored as the @@obj@@ function of @@controller.optimizer).

Note that, by default, the @@toMatlab@@ method exports the full open-loop optimizer. In the case of explicit MPC this implies that the output of @@z=name_of_file(x)@@ will be an {$ N \times n_u $} vector, where {$ N $} is the prediction horizon and {$ n_u $} is the number of control inputs. Then the closed-loop control action is given by @@u = z(1:nu)@@. Alternatively, you can ask @@toMatlab()@@ to only export the closed-loop optimizer. This can be achieved by:
(:source lang=MATLAB :) [@
solution.trimFunction('primal', nu);
solution.toMatlab('name_of_file.m', 'primal', 'obj')
@]
Here, @@trimFunction('primal', nu)@@ will change the @@primal@@ function such that it only returns the closed-loop optimizer (i.e., the first @@nu@@ components of the open-loop optimizer).

Full example:
(:source lang=MATLAB :) [@

Changed lines 65-67 from:

@]

to:

@]

!! Export to C code

November 01, 2013, at 08:50 AM by mk -

Added lines 1-38:

! Code generation

MPT3 allows to export parametric solutions in two ways:
# Export to pure Matlab code
# Export to C code

!! Important note

This feature is currently only available in development releases of MPT3. To install the latest development version, run the following:
(:source lang=MATLAB :) [@
tbxmanager source add http://www.tbxmanager.com/package/unstable.xml/mpt
tbxmanager update
@]

!! Export to pure Matlab code

Arbitrary parametric solutions can be exported to a standalone m-file by the @@PolyUnion/toMatlab@@ method. Example:
(:source lang=MATLAB :) [@
% prediction model
model = LTISystem('A', [1 1; 0 1], 'B', [1; 0.5]);
model.x.min = [-5; -5];
model.x.max = [5; 5];
model.u.min = -1;
model.u.max = 1;
model.x.penalty = QuadFunction(eye(2));
model.u.penalty = QuadFunction(1);
% prediction horizon
N = 5;
% construct the explicit MPC controller
ctrl = MPCController(model, N).toExplicit();

% export the explicit solution to a standalone m-file
ctrl.optimizer.toMatlab('mycontroller.m', 'primal', 'obj');

% evaluate the exported solution for a particular state
x0 = [2; 1];
[U, region] = mycontroller(x0);
@]

Codegen

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