In this paper, a new algorithm to build an optimal input for state reconstruction in the class of state-affine systems is proposed, in the sense that it enhances the performances of a Kalman-like observer, as well as it guarantees the system observability. The approach relies on the fact that for a state-affine system, as soon as the input is defined as a function of time, Kalman filtering theory can be applied. In fact, it is first highlighted how an appropriate choice of the system input can improve the Kalman filtering performance in this case. It is then emphasized how this input selection amounts to a control problem, which can be solved by an appropriate optimization algorithm. Finally, the algorithm is applied to a case of fault detection in a pipeline as an illustrative example, with some simulation results showing the observer performance improvement with the proposed input.
Automatica – Elsevier
Published: Jul 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera