Sil/pil test of matlab code generation

One 、SIL And PIL Testing process

1.SIL（Software in the Loop）, Use SIL Can be in PC End test generated code .   PIL（Processor in the Loop）, Use PIL It can be used in the actual target hardware or instruction set simulator   Run the source code on to test .

  Test standard ： take PIL（SIL） The results were compared with the normal model test results contrast , You can get the execution effect of the generated code .

2. Configuration and PC Direct connection parameters of the end

Two 、Top Model Of SIL/PIL Simulation

characteristic ：

1. You can directly use an independent code interface for testing
2. Models can be configured from Workspace Load test vector and excitation input
3. Conveniently in Top model、Normal、SIL、PIL Switch between

The official link ： The official link 1

stay matlab command window Enter the following command :

model='rtwdemo_sil_topmodel';
close_system(model,0)    // Close without saving 
open_system(model)		// open model

After the Simulink Open the following model ：

stay matlab command window Enter the following command :

set_param(gcs, 'RecordCoverage','off');                            /* Close the model coverage record */
coverageSettings = get_param(model, 'CodeCoverageSettings');      
coverageSettings.CoverageTool='None';							   /* Turn off code coverage logging */
set_param(model, 'CodeCoverageSettings',coverageSettings);
set_param(model, 'CodeExecutionProfiling','off');				  /* Turn off execution time analysis */

[ticks_to_count, reset, counter_mode, count_enable] = ...
    rtwdemo_sil_topmodel_data(T);                                   /* Set input parameters */
    
set_param(model, 'LoadExternalInput','on');
set_param(model, 'ExternalInput','ticks_to_count, reset, counter_mode, count_enable');
set_param(model, 'SignalLogging', 'on');
set_param(model, 'SignalLoggingName', 'logsOut');				   /* Set related parameters */

set_param(model,'SimulationMode','normal')
[~, ~, yout_normal] = sim(model,10);                               /* function normal  Model （ The results are stored in yout_normal）*/

set_param(model,'SimulationMode','Software-in-the-Loop (SIL)') 
[~, ~, yout_sil] = sim(model,10);                                  /* function SIL Model （ The results are stored in yout_sil）*/


fig1 = figure;
subplot(3,1,1), plot(yout_normal), title('Counter Output for Normal Simulation')
subplot(3,1,2), plot(yout_sil), title('Counter Output for SIL Simulation')
subplot(3,1,3), plot(yout_normal-yout_sil), ...    
    title('Difference Between Normal and SIL');                       /* The plot , Watch the difference */

Relevant settings in the model ：

  The execution of the whole model is , Input control parameters from the outside and execute , Then contrast SIL And normal Analyze the operation results under the model .

3、 ... and 、 Model based SIL(PIL) test

model='rtwdemo_sil_modelblock';
open_system(model);                    /* Open model */

coverageSettings = get_param(model, 'CodeCoverageSettings');
coverageSettings.CoverageTool='None';
set_param(model, 'CodeCoverageSettings',coverageSettings);
open_system('rtwdemo_sil_modelblock')
set_param('rtwdemo_sil_modelblock', 'CodeExecutionProfiling','off');
open_system('rtwdemo_sil_counter')
set_param('rtwdemo_sil_counter', 'CodeExecutionProfiling','off');
currentFolder=pwd;
save_system('rtwdemo_sil_counter', fullfile(currentFolder,'rtwdemo_sil_counter.slx')) 
/* Turn off code coverage 、 Execution time analysis */

set_param([model '/CounterA'], 'CodeInterface', 'Top model');     /* Set the operation mode of the model */
out = sim(model,20);                /* Began to run */

yout = find(out,'logsOut');
yout_sil = yout.get('counterA').Values.Data;
yout_normal = yout.get('counterB').Values.Data;
fig1 = figure;
subplot(3,1,1), plot(yout_normal), title('Counter Output for Normal Simulation')
subplot(3,1,2), ...
    plot(yout_sil), title('Counter Output for Model Block SIL (Top-Model) Simulation')
subplot(3,1,3), plot(yout_normal-yout_sil), ...
    title('Difference Between Normal and SIL');                   /* Draw a chart for analysis */

  This mode is normal and SIL（PIL） They are encapsulated into a test module and executed at the same time （ As shown in figure of CounterA And CounterB）, Compare the results after implementation .

Four 、 be based on SIL(PIL) Control module test

model='rtwdemo_sil_block';
close_system(model,0)
open_system(model)                  /* Open model */

out = sim(model,10);
yout_normal = find(out,'yout');
clear out                          /* Startup model */   Here is normal Simulation of the model 

set_param(model,'CreateSILPILBlock','SIL');
close_system('untitled',0);
rtwbuild([model '/Controller'])

controllerBlock = [model '/Controller'];
blockPosition = get_param(controllerBlock,'Position');
delete_block(controllerBlock);
add_block('untitled/Controller',[controllerBlock '(SIL)'],...
          'Position', blockPosition);
close_system('untitled',0);
clear controllerBlock blockPosition

Then a new model Build box ：

controllerBlock = [model '/Controller'];
blockPosition = get_param(controllerBlock,'Position');
delete_block(controllerBlock);                                          // Delete the module in the original model 

add_block('untitled/Controller',[controllerBlock '(SIL)'],...           // The generated Model Replace the module in the original model 
          'Position', blockPosition);
close_system('untitled',0);
clear controllerBlock blockPosition

out = sim(model,10);                                                    // Start the simulation 

machine_precision = eps(single(yout_normal));
tolerance = 4 * machine_precision;                                      // Set the simulation tolerance 

yout_sil = find(out,'yout');
tout = find(out,'tout');
fig1 = figure;
subplot(3,1,1), plot(yout_normal), title('Controller Output for Normal Simulation')
subplot(3,1,2), plot(yout_sil), title('Controller Output for SIL Simulation')
subplot(3,1,3), plot(tout,abs(yout_normal-yout_sil),'g-', tout,tolerance,'r-'), ...
    title('Normal and SIL Difference and Error Tolerance');                // The plot 
    
    
close_system(model,0);
if ishandle(fig1), close(fig1), end
clear fig1
simResults={'out','yout_sil','yout_normal','tout','machine_precision'};
save([model '_results'],simResults{:});
clear(simResults{:},'simResults')                                          // Close image 

5、 ... and 、 summary

PIL Testing , You can verify the test generated code .C2000 The test of is similar to the above , The specific description link is as follows ： The official link