Arbeitspapier
Reducing the Dimensionality of Linear Quadratic Control Problems
In linear-quadratic control (LQC) problems with singular control cost matrix and/or singular transition matrix, we derive a reduction of the dimension of the Riccati matrix, simplifying iteration and solution. Employing a novel transformation, we show that, under a certain rank condition, the matrix of optimal feedback coefficients is linear in the reduced Riccati matrix. For a substantive class of problems, our technique permits scalar iteration, leading to simple analytical solution. By duality the technique can also be applied to Kalman filtering problems with a singular measurement error covariance matrix.
- Sprache
-
Englisch
- Erschienen in
-
Series: Tinbergen Institute Discussion Paper ; No. 01-043/2
- Klassifikation
-
Wirtschaft
Optimization Techniques; Programming Models; Dynamic Analysis
Computational Techniques; Simulation Modeling
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- Thema
-
Linear-quadratic control
Riccati equation
Riccati reduction
Kalman filtering
Intertemporal optimization
Kontrolltheorie
Mathematische Optimierung
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Balvers, Ronald J.
Mitchell, Douglas W.
- Ereignis
-
Veröffentlichung
- (wer)
-
Tinbergen Institute
- (wo)
-
Amsterdam and Rotterdam
- (wann)
-
2001
- Handle
- Letzte Aktualisierung
- 10.03.2025, 10:41 UTC
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Balvers, Ronald J.
- Mitchell, Douglas W.
- Tinbergen Institute
Entstanden
- 2001
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