A Modeling and Filtering Framework for Linear Differential-Algebraic Equations
2003 (English)In: Proceedings of the 42th IEEE Conference on Decision and Control, 2003, 892-897 vol.1 p.Conference paper (Refereed)
General approaches to modeling, for instance using object-oriented software, lead to differential-algebraic equations (DAE). As the name reveals, it is a combination of differential and algebraic equations. For state estimation using observed system inputs and outputs in a stochastic framework similar to Kalman filtering, we need to augment the DAE with stochastic disturbances ("process noise"), whose covariance matrix becomes the tuning parameter. We will determine the subspace of possible causal disturbances based on the linear DAE model. This subspace determines all degrees of freedom in the filter design, and a Kalman filter algorithm is given. We illustrate the design on a system with two interconnected rotating masses.
Place, publisher, year, edition, pages
2003. 892-897 vol.1 p.
Implicit systems, Descriptor systems, Singular systems, White noise, Noise, Discretization, Kalman filters
National CategoryEngineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-13917DOI: 10.1109/CDC.2003.1272679ISI: 000189434100154ISBN: 0-7803-7924-1OAI: oai:DiVA.org:liu-13917DiVA: diva2:22190
42nd IEEE Conference on Decision and Control, Maui, HI, USA, December, 2003