Journal
ISA TRANSACTIONS
Volume 75, Issue -, Pages 101-117Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2018.02.007
Keywords
Adaptive Kalman filtering; Three-stage extended Kalman filtet; Nonlinear systems; Unknown inputs; Stability analysis
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Funding
- National Natural Science Foundation of China [11501022]
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Considering the performances of conventional Kalman filter may seriously degrade when it suffers stochastic faults and unknown input, which is very common in engineering problems, a new type of adaptive three-stage extended Kalman filter (AThSEKF) is proposed to solve state and fault estimation in nonlinear discrete-time system under these conditions. The three-stage U-V transformation and adaptive forgetting factor are introduced for derivation, and by comparing with the adaptive augmented state extended Kalman filter, it is proven to be uniformly asymptotically stable. Furthermore, the adaptive three-stage extended Kalman filter is applied to a two-dimensional radar tracking scenario to illustrate the effect, and the performance is compared with that of conventional three stage extended Kalman filter (ThSEKF) and the adaptive two-stage extended Kalman filter (ATEKF). The results show that the adaptive three-stage extended Kalman filter is more effective than these two filters when facing the nonlinear discrete-time systems with information of unknown inputs not perfectly known. (C) 2018 ISA. Published by Elsevier Ltd. All rights reserved.
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