Eigenvalues and Eigenvectors - How do I work out which eigenvalue corresponds to which eigenvector?
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I have a 7-DOF vibrating car model and would like to work out the eigenvalues (or natural frequencies) of each individual mode of the car, where the body has 3-DOF (pitch, roll and vertical displacement) and then each wheel has 1-DOF for its vertical displacement. I have pre-defined the mass and stiffness matrices so that I can find the eigenvectors and eigenvalues using "[Evecs,Evals]=eig(inv(M)*K)", which gives me matrices containing the eigenvectors and eigenvalues.
The problem I have is that the Evals matrix is mixed up, such that I do not know for definite which eigenvalue corresponds to which eigenvector. Because the car is assumed symmetric across its width, I can easily work out the three body modes but I do not know how to distinguish between the four wheel modes.
This issue only seems to occur with high-DOF systems, as I have successfully performed the exact same method on a 4-DOF half-car model. Has anyone else encountered this problem? Is there an easy way for me to resolve it?
4 comentarios
Steven Lord
el 11 de Abr. de 2017
Or solve the generalized eigenvalue problem directly using eig(K, M).
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John D'Errico
el 11 de Abr. de 2017
Editada: John D'Errico
el 11 de Abr. de 2017
I see from your comments to Jan that you still want an answer on how to know or fix the order of the eigenvalues. In your words:
"As you should be able to see, the way I have defined my mass and stiffness matrices implies that the eigenvalues should be arranged in this order: body vertical mode, body roll mode, body pitch mode, front left wheel mode, front right wheel mode, rear right wheel mode, rear left wheel mode. "
NO. You cannot know that the eigenvalues & eigenvectors are in any order that corresponds to specific things about your system. If that happens SOMETIMES, then you got lucky! It need not happen in general, nor should you presume that it will ever happen.
The eigenvalues are essentially the roots of a polynomial. At least, you can think of them that way, regardless of how they end up being computed. They need not correspond to any physical features of your system, and there is no presumption of order.
3 comentarios
John D'Errico
el 11 de Abr. de 2017
Eigenvectors rarely have simple meanings that you can attribute to them. If you get lucky, you may see something that makes sense for some eigenvectors, when you think about the linear combination of the parameters that they imply.
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