Rapid Control Application Environment - Goals
The steps to provide full featured rapid control applications development systems
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recommended project tasks (suggested to be committing) -
install pysimCoder -
reproduce generation of native Linux RT application from model, run without RT priority (-p -1) -
reproduce building and running application with SHV included again pisa-virt server -
optional try compile Qt libshv and spy on your computer
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setup pyshv and test pyshv proker with python client -
test pysimCoder generated application against pyshv broker -
use pyshv client code to write simple application demonstrating parameters tuning in running model -
test this application to connect to application over pisa-virt Qt broker -
#4 integrate pyshv client in pysimCoder and add actions to the the block context menu to open dialog to tune parameters from pysimCoder -
add the another context menu entry to add block into the list of inputs and outputs to monitor
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pysimCoder parameters match to the online tunable ones -
pysimCoder modifications -
ability to use blocks provided python functions not only in generation step but even during diagram editing -
correct hierarchy and subsystems representation
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pysimCoder vector signal -
signal widths propagation and resolution, probably use sympy
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rewrite pysimCoder core into Qt -
demo tasks -
SaMoCon target, PMSM control (NuttX) -
CAN communication
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MZ_APO target DC motor and follower target (RTEMS) -
CAN FD support
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MZ_APO target DC motor and follower target (GNU/Linux RT) -
CAN communication
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MZ_APO target PMSM control (GNU/Linux RT) -
CAN communication
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Raspberry Pi DC motor (GNU/Linux RT) -
Raspberry Pi PMSM motor (GNU/Linux RT) -
ICE-V (ESP32C3) DC motor or PMSM demo (NuttX, demo only system performance insufficient for serious results) -
CAN communication -
advanced FPGA design
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Educational models on GNU/Linux RT on x86 with COMEDI support -
AutomationShield -
ARI BegleBone platform, inverted pendulum
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