- AutorIn
- Peter Benner
- Sabine Hein
- Titel
- Model predictive control based on an LQG design for time-varying linearizations
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:ch1-201000221
- Schriftenreihe
- Chemnitz Scientific Computing Preprints
- Bandnummer
- 09-07
- ISSN
- 1864-0087
- Abstract (EN)
- We consider the solution of nonlinear optimal control problems subject to stochastic perturbations with incomplete observations. In particular, we generalize results obtained by Ito and Kunisch in [8] where they consider a receding horizon control (RHC) technique based on linearizing the problem on small intervals. The linear-quadratic optimal control problem for the resulting time-invariant (LTI) problem is then solved using the linear quadratic Gaussian (LQG) design. Here, we allow linearization about an instationary reference trajectory and thus obtain a linear time-varying (LTV) problem on each time horizon. Additionally, we apply a model predictive control (MPC) scheme which can be seen as a generalization of RHC and we allow covariance matrices of the noise processes not equal to the identity. We illustrate the MPC/LQG approach for a three dimensional reaction-diffusion system. In particular, we discuss the benefits of time-varying linearizations over time-invariant ones.
- Andere Ausgabe
- Link: http://www.tu-chemnitz.de/mathematik/csc/preprints.php
- Freie Schlagwörter
- LTV systems
- incomplete observations
- linear quadratic Gaussian design
- model predictive control
- noise
- receding horizon control
- Klassifikation (DDC)
- 510
- Normschlagwörter (GND)
- Nichtlineares System
- Optimale Kontrolle
- Publizierende Institution
- Technische Universität Chemnitz, Chemnitz
- Förder- / Projektangaben
- URN Qucosa
- urn:nbn:de:bsz:ch1-201000221
- Veröffentlichungsdatum Qucosa
- 11.03.2010
- Dokumenttyp
- Preprint
- Sprache des Dokumentes
- Englisch