Rapid Accelerator tunable parameters mapping structure remains empty after build
5 Ansichten (letzte 30 Tage)
I am trying to to learn how to tune parameters of a rapid accelerator model that I want to build. For starters I followed Getting the most out of Rapid Accelerator mode. Using R2015a, I opened up the "sldemo_bounce"-model, enabled the Inline parameters option under Configuration parameters --> Optimization --> Signals and Parameters and saved it under a new name ("bounce_demo"). The code I am trying to run looks like this:
k = Simulink.Parameter;
k.CoderInfo.StorageClass = 'SimulinkGlobal';
k.Value = -0.9;
mdl = 'bounce_demo'; % Renamed version of "sldemo_bounce" with Inline Paremeters enabled, nothing else changed
rtp = Simulink.BlockDiagram.buildRapidAcceleratorTarget(mdl,'AddTunableParamInfo','on');
The model compiles without warnings/errors, but rtp.parameters.map is empty (= ). rtp.parameters.value has all the values of the bouncing ball model, but somehow the corresponding mapping field does not hold the variable names. So when I try to change the variable "k" according to the above mentioned example by
k_values = [-0.9:0.1:-0.1];
for i = 1:length(k_values)
paramSet(i) = Simulink.BlockDiagram.modifyTunableParameters(rtp, 'k', k_values(i));
it does not work as "k" is not defined within the rtp-structure (Error using modifyRTP The rtp structure passed in did not have a parameter k).
So is there any setting I am unaware of or the author has forgotten to mention in the above article to make it work?
Also I am unsure at what point the actual executable (.exe) is created as so far none has been created. Only the "slprj"-folder is created.
Any feedback is highly appreciated.
Tong Zhao am 16 Feb. 2022
I had a similar problem, and here's how I resolved it:
In my Simulink model, the tunable parameters I provided did not contribute to the output of the model, and that was why the error popped out:
Error using modifyRTP
The rtp structure passed in did not have a parameter ACC_ADJ
Then I corrected the mistake, and made sure that the tunable parameter I have will affect the output of the model. Then everything worked fine.
Hope this helps.