LQR Error about controllability

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Usman Shahzad
Usman Shahzad el 2 de Dic. de 2012
Comentada: 嘉俊 黄 el 21 de Mzo. de 2022
Hi everyone,
I am doing some work on LQR controller for time variant system. My problem is that by choosing the weights Q and R some of my states get worked but some does not. MATLAB gives the error that:
The "lqr" command failed to stabilize the plant or find an optimal feedback gain. To remedy this problem:
1. Make sure that all unstable poles of A are controllable through B (use MINREAL to check)
2. Modify the weights Q and R to make [Q N;N' R] positive definite (use EIG to check positivity).
My question is how i can remove this problem as [Q N;N' R] is sure positive definite and my system is controllable as well.
thanks
  1 comentario
Muhammad Ali
Muhammad Ali el 2 de Nov. de 2014
I am facing the same problem as Usman suggested. Please someone answer the queries. Thnx

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Respuestas (2)

Ursula
Ursula el 24 de Mayo de 2013
Editada: Ursula el 24 de Mayo de 2013
Hi,
I have the same problem. The error message appears, although my system is controllable, and my [Q N;N' R] is positive definite. If I want to get the controller with pole placement, Matlab says:
The "place" command could not place the poles at the specified locations.
Probable causes include:
* (A,B) is nearly uncontrollable
* The specified locations are too close to each other.
The specified locations are at -1, -2, -3, ... -59, and there is no other result, if I increase the space between the desired poles.
My System is of 59th order. The maximum value of Matrix A is 3e+006 and the Controllability Matrix of (A,B) has maximum value of 3e+120. Is this maybe a numerical problem, and how can I solve it?
  3 comentarios
Sam Chak
Sam Chak el 21 de Mzo. de 2022
Hi @嘉俊 黄 (Mr. Wong)
You are advised to post a new question on the LQR design problem that your are facing, on the grounds that the users have been inactive since 2013. Most likely, you won't get any useful response from them.
If there is no sensitive information, it is preferrable to show the State Matrix , the Input Matrix , and the weights , , in the cost function.
Thanks for considering this advice.
嘉俊 黄
嘉俊 黄 el 21 de Mzo. de 2022
OK,Thank you!

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Leonardo Costa
Leonardo Costa el 31 de En. de 2021
Hi, I'm facing the same problem! Did you solve it?

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