MENÜ MENÜ  

cover

Proximity Moving Horizon Estimation

Meriem Gharbi

ISBN 978-3-8325-5456-9
174 pages, year of publication: 2022
price: 45.00 €
Proximity Moving Horizon Estimation
In this thesis, we develop and analyze a novel framework for moving horizon estimation (MHE) of linear and nonlinear constrained discrete-time systems, which we refer to as proximity moving horizon estimation. The conceptual idea of the proposed framework is to employ a stabilizing a priori solution in order to ensure stability of MHE and to combine it with an online convex optimization in order to obtain an improved performance without jeopardizing stability. The goal of this thesis is to provide proximity-based MHE approaches with desirable theoretical properties and for which reliable and numerically efficient algorithms allow the estimator to be applied in real-time applications.

In more detail, we present constructive and simple MHE design procedures which are tailored to the considered class of dynamical systems in order to guarantee important properties of the resulting estimation error dynamics. Furthermore, we develop computationally efficient MHE algorithms in which a suboptimal state estimate is computed at each time instant after an arbitrary and limited number of optimization algorithm iterations. In particular, we introduce a novel class of anytime MHE algorithms which ensure desirable stability and performance properties of the estimator for any number of optimization algorithm iterations, including the case of a single iteration per time instant.

In addition to the obtained theoretical results, we discuss the tuning of the performance criteria in proximity MHE given prior knowledge on the system disturbances and illustrate the theoretical properties and practical benefits of the proposed approaches with various numerical examples from the literature.

cover cover cover cover cover cover cover cover cover
Table of contents (PDF)

Preview (PDF)

Keywords:

  • Moving horizon estimation
  • Stability
  • Performance
  • Optimization algorithms

BUYING OPTIONS

45.00 €
in stock

42.00 €
55.00 €
59.00 €

(D) = Within Germany
(W) = Abroad

*You can purchase the eBook (PDF) alone or combined with the printed book (eBundle). In both cases we use the payment service of PayPal for charging you - nevertheless it is not necessary to have a PayPal-account. With purchasing the eBook or eBundle you accept our licence for eBooks.

For multi-user or campus licences (MyLibrary) please fill in the form or write an email to order@logos-verlag.de