In responding to the post by "gabrielgga" about system linearization, I
looked at the 'lin' script to understand it.  It does the linearization
by generating a set of random perturbation vectors, perturbing the
system, and then numerically solving for the Jacobians.  As such, it
coughs up a slightly different linearization each time.  The
linearization is largely accurate, but the difference from ideal is more
than I'd (perhaps naively) expect.

Why?  If this is a well-known technique, please feel free to point me at
a paper.


Tim Wescott
Control & Communications systems, circuit & software design.
Phone: 503.631.7815
Cell:  503.349.8432

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