Fast moving horizon estimation using multi-level iterations for microgrid control
Author:
Affiliation:
1. Interdisciplinary Center for Scientific Computing (IWR) , Heidelberg University , Heidelberg , Germany
2. Siemens AG , Munich , Germany
Abstract
Funder
Bundesministerium für Bildung und Forschung
Publisher
Walter de Gruyter GmbH
Subject
Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering
Link
https://www.degruyter.com/document/doi/10.1515/auto-2020-0081/pdf
Reference28 articles.
1. A. Alessandri and M. Gaggero. Fast moving horizon state estimation for discrete-time systems using single and multi iteration descent methods. IEEE Transactions on Automatic Control, 62(9):4499–4511, 2017.
2. I. Bauer, H.G. Bock, and J.P. Schlöder. DAESOL – A BDF-code for the numerical solution of differential algebraic equations. Internal report, IWR, SFB 359, Universität Heidelberg, 1999.
3. K. Baumgartner, A. Zanelli and M. Diehl. Zero-order moving horizon estimation. In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019.
4. V.M. Becerra, P.D. Roberts and G.W. Griffiths. Applying the extended Kalman filter to systems described by nonlinear differential-algebraic equations. Control Engineering Practice, 9(3):267–281, 2001.
5. H.G. Bock. Randwertproblemmethoden zur Parameteridentifizierung in Systemen nichtlinearer Differentialgleichungen, volume 183 of Bonner Mathematische Schriften. Universität Bonn, Bonn, 1987.
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