# Control of inverted pendulum

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AG 2019년 11월 18일
답변: AG 2019년 12월 5일
Hello everyone,
I'm playing with the Inverted Pendulum example : openExample('simulink_general/penddemoExample') in Command Window. I'm trying to understand which control theory stays behind the state space estimator and the choice of LQR parameters.
I don't find anything similar in literature, can anyone help me, please?

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### 답변 (2개)

M 2019년 11월 18일
I don't find anything similar in literature
LQR algorithm with state estimator is very common and you can find plenty of examples in the literature.
In the simulink example, the state space estimator is implemented with a discrete time state space equation:
And the LQR block is simply a matrix gain. You can find details about lqr in matlab here:
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M 2019년 11월 20일
I did not look into details but it looks like the matrices inside the estimator block come from a linearization of the functions that model the cart + pendulum. I guess the linearization is made around the vertical position.
AG 2019년 11월 22일
Its look like we use the information of cart position and angle sensor "as is", the meaning of A=0 is that we don't consider the previous state but I don't understand why. If I linearize the generic model of a inverted pendulum on a cart I must use the general model where A is a 4x4 matrix and not 2x2.

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AG 2019년 12월 5일
No one could help me?
Thank you very much!

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