Abstract
In this chapter we shall address topics dealing with adding robustness to the design of reduced order filters. We will show how one can treat a broad range of noise or disturbance terms characterized as having bounded energy, rather than as having white noise characteristics. For such additive arbitrary disturbances, we show how to guarantee a bound on the ratio of the energy in the error to the energy in the disturbances. In [1], a rigorous derivation of the results contained here was developed. We will present here, a derivation based on game theory which more closely corresponds to the calculus of variations approach taken throughout this text, and follows the method suggested by Banavar and Speyer [2].
Keywords
- Kalman Filter
- Riccati Equation
- Reduce Order Model
- Full Order
- Matrix Riccati Equation
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Jalali, A.A., Sims†, C.S., Famouri, P. 10 Robust Reduced Order Filtering. In: Reduced Order Systems. Lecture Notes in Control and Information Science, vol 343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11597018_10
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DOI: https://doi.org/10.1007/11597018_10
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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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