Study on initial value problem for fractional-order cubature Kalman filters of nonlinear continuous-time fractional-order systems

Yang, Chuang; Gao, Zhe; Miao, Yue; Kan, Tao

doi:10.1007/s11071-021-06726-3

Cited by 8 publications

(2 citation statements)

References 35 publications

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“…Although the KF is an optimal estimation method when the various errors mentioned above follow a Gaussian distribution, there may be divergence or distortion due to errors or initial values [27] in the linearization of the nonlinear models. In addition, in this study, the number of observations is limited; we believe that the prior knowledge of the velocity vectors is not necessarily accurate.…”

Section: Kalman Filteringmentioning

confidence: 99%

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization

Luo

Chu³

et al. 2023

Sensors

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In a single-observer passive localization system, the velocity and position of the target are estimated simultaneously. However, this can lead to correlated errors and distortion of the estimated value, making independent estimation of the speed and position necessary. In this study, we introduce a novel optimization strategy, suboptimal estimation, for independently estimating the velocity vector in single-observer passive localization. The suboptimal estimation strategy converts the estimation of the velocity vector into a search for the global optimal solution by dynamically weighting multiple optimization criteria from the starting point in the solution space. Simulation verification is conducted using uniform motion and constant acceleration models. The results demonstrate that the proposed method converges faster with higher accuracy and strong robustness.

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Section: Kalman Filteringmentioning

confidence: 99%

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization

Luo

Chu³

et al. 2023

Sensors

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“…Two fractional‐order cubature Kalman filter algorithms were presented in ref. [35], which significantly lessens the influence of the initial value. An initial state estimate approach was presented in ref.…”

Section: Introductionmentioning

confidence: 99%

An Initial Value Problem for State of Charge Estimation of Lithium‐Ion Batteries with an Adaptive Fractional‐Order Unscented Particle Filter

Jiao,

Gao,

Chai

et al. 2023

Advcd Theory and Sims

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This paper proposes an adaptive fractional‐order unscented particle filter (AFOUPF) with the initial value compensation (IVC) to enhance the estimation accuracy of the state of charge (SOC) for lithium‐ion batteries (LIBs). First, to correctly reflect the dynamic properties of LIBs, a fractional‐order system (FOS) with a constant phase component is constructed. Second, to discretize the FOS equation of LIBs, the Grünwald–Letnikov difference, Caputo derivative and Rieman–Liouville difference are employed to establish the corresponding difference equation. Third, a map function is applied to keep the order and SOC of the FOS within an appropriate interval. Further, an approach of IVC is provided for the AFOUPF to increase the accuracy of SOC estimation, taking into account that the accuracy of SOC estimation is impacted if the order of the FOS is relatively small in (0, 1). By utilizing the augmented vector approach, the simultaneous estimations of order, parameters, initial value, and SOC are resolved. Besides, an iterative approach that accommodates the noise covariance matrices is proposed to improve the estimation accuracy. The AFOUPF conducts an unscented transform and resampling on each particle, resulting in a high SOC estimation accuracy in complicated situations. Finally, the availability of AFOUPF is tested by several experiments.

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Gaussian process regression combined with dynamic data reconciliation for improving the performance of nonlinear dynamic systems

Hu¹,

Xu²,

Zhang³

2023

Nonlinear Dyn

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Study on initial value problem for fractional-order cubature Kalman filters of nonlinear continuous-time fractional-order systems

Cited by 8 publications

References 35 publications

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization

An Initial Value Problem for State of Charge Estimation of Lithium‐Ion Batteries with an Adaptive Fractional‐Order Unscented Particle Filter

Gaussian process regression combined with dynamic data reconciliation for improving the performance of nonlinear dynamic systems

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