Dual control and online optimal experimental design

• Verfasst von: La, Huu Chuong [VerfasserIn]
• Verfasst von: Potschka, Andreas [VerfasserIn]
• Verfasst von: Schlöder, Johannes P. [VerfasserIn]
• Verfasst von: Bock, Hans Georg [VerfasserIn]
• Titel: Dual control and online optimal experimental design
• Verf.angabe: H. La, A. Potschka, J. Schlöder, and H. Bock
• Umfang: 18 S.
• Fussnoten: Gesehen am 29.01.2018
• Titel Quelle: Enthalten in: Society for Industrial and Applied Mathematics: SIAM journal on scientific computing
• Jahr Quelle: 2017
• Band/Heft Quelle: 39(2017), 4, S. B640-B657
• ISSN Quelle: 1095-7197
• DOI: doi:10.1137/16M1069936
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1567756352

Abstract

Dual control refers to strategies that strike a balance between control and estimation. Combined with nonlinear model predictive control, dual control offers advanced feedback methods for optimal control problems under uncertainties. We present dual control from a new perspective, namely, the interplay between the performance control task and the information gain task in connection with optimal experimental design. A new approach to dual control is proposed in which the covariance matrix of the estimates is weighted by the derivatives of the nominal objective value with respect to unknown parameters and initial states.