Iterative identification and control using a weighted q-Markov cover with measurement noise Academic Article

abstract

• An identifiability result determines whether there exists a linear time-invariant model capable of matching certain input/output data observed from experiments with measurement noise. If no match is possible, a method is presented to find the closest linear model to the data. A weighted q-Markov COVER method is introduced for identification with measurement noise. These results are used to develop an iterative closed-loop identification/control design algorithm.

authors

• Skelton, Robert

published proceedings

• Signal Processing

author list (cited authors)

• Skelton, R. E., & Shi, G.

citation count

• 12

complete list of authors

• Skelton, RE||Shi, G

publication date

• July 1996

publisher

• Elsevier  Publisher

published in

• Signal Processing  Journal

keywords

• Bioengineering

Digital Object Identifier (DOI)

• 10.1016/0165-1684(96)00055-2

start page

• 217

end page

• 234

volume

• 52

issue

• 2

URL

• http://dx.doi.org/10.1016/0165-1684(96)00055-2