for HammersteinWiener systems in errorsinvariables framework Malgorzata Sumislawska Prof Keith J Burnham Coventry University UKACC PhD Presentation Showcase UKACC PhD Presentation Showcase ID: 674033
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Slide1
Parity equations-based unknown input reconstruction for Hammerstein-Wiener systems in errors-in-variables framework
Malgorzata SumislawskaProf Keith J Burnham Coventry University
UKACC PhD Presentation ShowcaseSlide2
UKACC PhD Presentation Showcase
Slide 2Motivation
Errors-in-variables (EIV) frameworkInput and output
signals are subjected to white, Gaussian, zero-mean, mutually uncorrelated measurement noise
sequences
Long history of research on EIV framework in Control Theory and Applications Centre
Aim: reconstruct unknown
input while
minimising impact ----of measurement noise on unknown input estimateSlide3
UKACC PhD Presentation Showcase
Slide 3Motivation
Hammerstein-Wiener (HW) system representation considered
Relatively simple model structure Can approximate large class of nonlinear systems
Limited attention paid to HW systems in EIV framework
N
1
(
.) , N2(.
) – static nonlinear functionsSlide4
UKACC PhD Presentation Showcase
Slide 4Problem solution
Knowing N
1(.
)
and
N
2
(.) calculate input and output to linear dynamic blockInput and output estimates to linear block affected by noise
signals to
be calculatedSlide5
UKACC PhD Presentation Showcase
Slide 5Problem solution
Knowing N
1(.
)
and
N
2
(.) calculate input and output to linear dynamic blockInput and
output estimates to linear block affected by noiseLinear EIV setup with
heteroscedastic
noise, whose variance depends on operating point
Need for adaptive schemeSlide6
UKACC PhD Presentation Showcase
Slide 6Problem solution
Influence of noise minimised using Lagrange multipliers optimisation method
Time-varying noise variances estimated from N
1
(
.
)
and N2(.
)
using Taylor expansion
Experimental (Monte-Carlo simulation) results
match
theoretical calculationsSlide7
UKACC PhD Presentation Showcase
Slide 7Summary and future work
SummaryNovel approach for unknown input reconstructi
on developed Effect of measurement noise minimised in adaptive manner
The work published in
Sumislawska
M., Larkowski, T., Burnham, K. J., ‘Unknown input reconstruction observer for Hammerstein-Wiener systems in the errors-in-variables', Proceedings of 16st IFAC Symposium on System Identification, Brussels, Belgium, 11-13 July 2012Future workColoured output noise Multivariable case