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I am working on a project in which I want to use State Feedback Control to position control a BLDC motor in combination with a motor controller. I want to do this since translating time domain specifications into controller gain using this method is way more exact than the heuristic method of PID tuning. I would run the current control PD on the microcontroller and the state feedback on a microcontroller. For this to work, a state space representation needs to be made of the whole BLDC system. Using the control scheme shown below, I wanted to determine the state space representation of the green box, where the current command is the input, as shown by the red arrow, and the motor position is the output. I have done much research and have found complicated versions which will require also modeling the inverter, or simple 2nd/3rd order systems.

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My questions are:

  1. What is the correct state space model to use?

  2. Would you advise to take the other approach of applying system identification methods to determine the state space?

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  • $\begingroup$ With the encoder are you measuring angle or speed? $\endgroup$ – morbo Aug 25 '19 at 12:25
  • $\begingroup$ Oh this is ultra old... $\endgroup$ – morbo Aug 25 '19 at 12:26
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There is probably no 100% correct/accurate (state space) model. You should consider what is your required precision and use the simplest model which fulfills your accuracy requirements. If you do not have a strict requirement start with the simplest one and if it is not sufficient, upgrade the model.

You can use system identification methods to find model parameters. If you want high accuracy for one specific motor, this would be a good way of improving model accuracy. It might also work well for one specific motor model, depending on manufactruing quality (or the consistency of the manufacturing quality). If you one to apply it to different motors you might need to redo the parameter identification process for each (or at least each motor model).

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