Simulink add-on for motor control algorithm development

August 31, 2020 //By Rich Pell
Motor control blockset for algorithm development
MathWorks has introduced an add-on product for Simulink - a MATLAB-based graphical programming environment - for designing and implementing motor control algorithms.

The Motor Control Blockset , says the company, enables motor control engineers to use reference examples and Simulink blocks for developing field-oriented control algorithms to spin brushless motors. The blockset extends the set of Simulink products for motor control design, enabling engineers to test algorithms with each design change, generate fast and compact ANSI/ISO C code, and use simulation to validate software, reducing certification testing cycles.

“Instead of a process where handwritten code is not verified until actual motor testing," says Arkadiy Turevskiy, product manager at  MathWorks, "engineers can use simulation and code generation to catch errors earlier and speed up their motor control development projects. Motor Control Blockset strengthens our support for motor control design, where teams report reducing up to 50% of project time when using Simulink to design and implement digital control systems."

The company says that it is working with motor control hardware providers to develop reference examples that support their motor control kits, starting with several Texas Instruments kits based on their C2000 real-time microcontrollers. Engineers using these kits can automatically estimate motor parameters, generate application code, and spin motors in minutes. Additionally, Motor Control Blockset can be used with Simulink Real-Time and Speedgoat real-time target machines for rapid control prototyping, including field-oriented control autotuning.

Motor Control Blockset includes:

  • Park, Clarke, space vector modulation, field weakening, maximum torque per amp, and other motor control algorithms optimized for generating fast, compact embedded code
  • Resolver decoder, Hall sensor decoder, Quadrature encoder decoder, and sliding mode observer for implementing sensored and sensorless motor control
  • Field-Oriented Control Autotuner block for automatically tuning current and speed loops of field-oriented control architectures
  • Instrumented tests to estimate motor parameters from experiments with motor hardware
  • Linear lumped-parameter average-value motor models for verifying control algorithms in closed-loop simulation
  • Reference applications showing how to quickly spin a motor with several motor control hardware kits

For more, see the company's free ebook: Introduction to Brushless


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