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A New Approach to Receding Horizon State Estimation for LTI Systems in the Presence of Non-uniform Sampled Measurements

Jhon A. Isaza-Hurtado*, John J. Martinez, and Hector A. Botero-Castro
International Journal of Control, Automation, and Systems, vol. 17, no. 3, pp.679-690, 2019

Abstract : "This paper proposes a recursive solution as an estimation strategy that incorporates non-uniform sampled measurements for a Linear Time-Invariant (LTI) Systems. The estimator is based on a modified Receding Horizon Estimator. The proposed approach allows system states to be recursively estimated, reducing estimation error by including measurements available at different sampling times, using a well-known structure. A discussion of the observability of the system in the presence of non-uniform measurements and the convergence conditions of the proposed estimator are also presented. Finally, numerical simulation demonstrates the effectiveness of the proposed estimator in comparison with a method using a Kalman filter with augmented state widely reported in the literature."

Keyword : Kalman filter, linear time-invariant system, non-uniform measurement, receding horizon, state estimation

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