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Robust Finite-Horizon Kalman Filtering for Uncertain Discrete-Time Systems

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2 Author(s)
Shady M. K. Mohamed ; School of Engineering and Information Technology, Centre for Intelligent Systems Research (CISR), Deakin University, Australia ; Saeid Nahavandi

In this note, we propose a design for a robust finite-horizon Kalman filtering for discrete-time systems suffering from uncertainties in the modeling parameters and uncertainties in the observations process (missing measurements). The system parameter uncertainties are expected in the state, output and white noise covariance matrices. We find the upper-bound on the estimation error covariance and we minimize the proposed upper-bound.

Published in:

IEEE Transactions on Automatic Control  (Volume:57 ,  Issue: 6 )