Erratum to “Adaptive Fading Memory Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors” [Aug 15 1857-1864]

Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

doi:10.1109/tns.2016.2517335

Cited by 2 publications

(8 citation statements)

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“…Abstract-In a recent paper ( The formulation of filtering (LMI Approach) is presented below as Theorem I [2] (where the notations have the same meaning as in [1], however new variables introduced are defined at their first appearance).…”

Section: Comments On "Adaptive Fading Memory Filter Design For Compenmentioning

confidence: 99%

“…The above filter will have a solution if and only if the following condition is satisfied at each time step : [1] On the basis of the above set of equations, the algorithm for fading memory based filter can be obtained, as Algorithm II. Algorithm II:…”

Section: Comments On Section V-a: Fading Memory [1]mentioning

confidence: 99%

“…5 [1] showing the schematic of platinum SPFD model, it is not possible to obtain the model equation (62). Some other corrections are listed in Table I. …”

Section: Comments On Section V-a: Fading Memory [1]mentioning

confidence: 99%

“…This note suggests corrections to the theory and applications presented in their paper.I. COMMENTS ON SECTION II:FILTERING (LMI APPROACH)[1] …”

mentioning

confidence: 99%

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Comments on “Adaptive Fading Memory H Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors”

Mishra

Shimjith

Tiwari

2016

IEEE Trans. Nucl. Sci.

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In a recent paper (Tamboli, et al. 2015), Tamboli, Duttagupta, and Roy have presented a comparative study of existing dynamic compensation algorithms based on Linear Matrix Inequality (LMI) based a priori filtering and Discrete time Algebric Riccati Equation (DARE) based Kalman filtering for delayed responding Self Powered Flux detectors (SPFD) with Vanadium and Platinum emitters. Moreover, authors have proposed an adaptive fading memory discrete time filter by modifying the well-known Game Theoretic filtering algorithm. This note suggests corrections to the theory and applications presented in their paper.

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Section: Comments On "Adaptive Fading Memory Filter Design For Compenmentioning

confidence: 99%

Section: Comments On Section V-a: Fading Memory [1]mentioning

confidence: 99%

“…5 [1] showing the schematic of platinum SPFD model, it is not possible to obtain the model equation (62). Some other corrections are listed in Table I. …”

Section: Comments On Section V-a: Fading Memory [1]mentioning

confidence: 99%

“…This note suggests corrections to the theory and applications presented in their paper.I. COMMENTS ON SECTION II:FILTERING (LMI APPROACH)[1] …”

mentioning

confidence: 99%

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Comments on “Adaptive Fading Memory H Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors”

Mishra

Shimjith

Tiwari

2016

IEEE Trans. Nucl. Sci.

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show abstract

“…When the uncertainty reaches a certain extent, the estimation accuracy of the Kalman filter will be reduced, and Kalman filter may even have divergence problems in serious cases [20]. Comparatively, the H∞ filter is not based on any assumption about the frequency spectrum characteristics of the signal, and it has better robustness than the Kalman filter [20,22,23,24,25,26,27,28,29,30,31,32]. In the H∞ filter, the H∞ norm is introduced to the filtering problem, and a filter is designed to ensure the minimum norm from disturbance input to filter error output [20,23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems

Lyu

Cheng

2017

Sensors

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Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method.

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Erratum to “Adaptive Fading Memory Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors” [Aug 15 1857-1864]

Cited by 2 publications

References 1 publication

Comments on “Adaptive Fading Memory H Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors”

Comments on “Adaptive Fading Memory H Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors”

A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems

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