Comments (2)
The control policy in equation 12 of the RAL17_Faessler paper is a linear state feedback.
To put it simple, you take the error of your states, [omega_des - omega_hat; eta_ref - eta_hat] and multiply it with your LQR gain matrix. We additionally correct with feed-forward (J* omega_dot_des) and gyroscopic effect compensation (+ omega_hat x J*omega_hat).
The statement that this behaves like a PD controller comes from the fact that we use the body rate (omega) and torques (eta) as state. Note that eta approximates omega's derivative without the gyroscopic terms, therefore we cover a linear feedback on omega (P-term) and it's derivative (D-term).
Does this answer your question?
It doesn't "combine" controllers. It is an LQR that behaves similar to a PD controller because it acts on the state and the (approximated) derivative.
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Thank you for your patient explaining ,it will really help me and i will think seriously .I think i need to learn ’Modern Control Theory‘ at first.
Thank you very much again!
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