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In this article a primal barrier interior-point method for moving horizon estimation (MHE) is presented. It exploits the structure of the KKT systems yielding an algorithm with linear complexity in the horizon length as opposed to cubically as in unstructured solvers. Ideas of square root covariance Kalman filtering are proposed in order to update covariance matrices occurring in the factorization...
Based on the optimal weighted fusion estimation algorithm in the linear minimum variance sense, a distributed information fusion state filter is given for a multi-sensor multi-delay system with colored measurement noise. The filtering error cross-covariance matrix between any two sensor subsystems for the multiple time-delay system is derived. The proposed distributed fusion filter has higher accuracy...
The present paper proposes a new adaptive Kalman filter-based multisensor fusion to satisfy the real time performance requirements. The adaptive scheme of Kalman filter based on fuzzy logic is developed to prevent the filter from divergence and to avoid the need of accurate knowledge of statistical values of noise for both process and measurement noises. To reach this objective, first each measurement...
Loss of information (observations) is a common problem in control and communication systems. Kalman filter is a versatile tool for state estimation, but would it still produce accurate estimation in such a case? In this paper we investigate this situation and propose several approaches to compensate the loss of information in employing Kalman filter to estimate the state of a system. Minimum error...
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