Abstract
Flexible space structures are often modeled by a large set of second order differential equations. A Kalman filter designed for such a model might not be a very practical idea because of the high dimensionality required and the associated complexity of implementation. Here we derive a class of reduced order filters which reduce the complexity of the design and filtering process. As an added feature, the reduced order filter performance is shown to be completely insensitive to system parameters for an important class of problems.
Keywords
- Kalman Filter
- Riccati Equation
- Observer Constraint
- Order Filter
- Reduce Order Observer
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Jalali, A.A., Sims†, C.S., Famouri, P. 9 Reduced Order Filtering for Flexible Space Structures. In: Reduced Order Systems. Lecture Notes in Control and Information Science, vol 343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11597018_9
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DOI: https://doi.org/10.1007/11597018_9
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34358-5
Online ISBN: 978-3-540-34359-2
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