Siddharth Jawahar, MathWorks
Motor Control Blockset™ provides reference examples and blocks for developing field-oriented control algorithms for brushless motors. The examples show how to configure a controller model to generate compact and fast C code for any target microcontroller (with Embedded Coder®). You can also use the reference examples to generate algorithmic C code and driver code for specific motor control kits.
The blockset includes Park and Clarke transforms, sliding mode and flux observers, a space-vector generator, and other components for creating speed and torque controllers. You can automatically tune controller gains based on specified bandwidth and phase margins for current and speed loops (with Simulink Control Design™).
The blockset lets you create an accurate motor model by providing tools for collecting data directly from hardware and calculating motor parameters. You can use the parameterized motor model to test your control algorithm in closed-loop simulations.
Motor Control Blockset lets you design and implement motor control algorithms for permanent magnet synchronous motors. The product provides fully assembled reference examples for sensored and sensorless field-oriented control algorithms.
You can use these examples to verify control algorithms through closed-loop desktop simulation and then use Embedded Coder to generate code for implementation on a microcontroller. The examples show how to use Park and Clarke transforms, space vector generator, PI controllers, maximum torque per amp and other control blocks provided by the product to implement field-oriented control algorithms.
The product provides sensor decoders for Hall sensors, quadrature encoders, and resolvers.
Sliding mode and flux observer blocks are provided for implementing sensorless control.
Motor Control Blockset provides prebuilt instrumented tests to estimate stator resistance, dq-axis inductances, and other parameters of your motor.
You can use these parameters to compute initial control gains of the current and speed loops. You can further fine-tune these gains using the Field-Oriented Control Autotuner block.
You can create accurate motor models by using the estimated motor parameters with the provided motor modeling blocks.
You can then combine these motor models with the Average-Value Inverter block and your Field-Oriented Control algorithm to create closed-loop simulation models.
You can also simulate your control algorithm against higher-fidelity plant models developed with Simscape Electrical, for example, to model switching effects in the inverter.
Once the control algorithm has been verified in closed-loop desktop simulation, you can generate fast, compact code and deploy it to your target microcontroller.
You can use a host model to control the target application by setting the reference speed, adjusting controller parameters, and monitoring motor speed, phase currents, and other signals.
For more information, please visit the Motor Control Blockset product page on mathworks.com and download a trial to check out the reference examples.
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