Efficient two-dimensional Haar$$^+$$ synopsis construction for the maximum absolute error measure

Kim, Jinhyun; Min, Jun‐Ki; Shim, Kyuseok

doi:10.1007/s00778-019-00551-2

Cited by 1 publication

(1 citation statement)

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“…e reorganized measurement is denoted as y i (t) for the i-th subsystem. In addition, to further analyze the performance of the proposed DWFASS method, the maximum absolute errors (MAE) [42] are obtained by…”

Section: Outputmentioning

confidence: 99%

Distributed State Estimation for Dynamic Positioning Systems with Uncertain Disturbances and Transmission Time Delays

Liu

Yao

et al. 2020

Complexity

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The dynamic positioning system of unmanned underwater vehicles (UUVs) is a complex and large-scale system mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. With the aid of the bio-inspired computing (BIC) method, the designed three-dimensional (3D) spatial positioning system is used for enlarging communication constraints and increasing signal coordination processing. With the growing of measurement scales, the issue of the networked high-precision positioning has been developed rapidly. Then, an information fusion estimation approach is presented for the distributed networked systems with data random transmission time delays and lost and disordered packets. To reduce the communication burden, an adaptive signal selection scheme is employed to reorganize the measurement sequence, and the parameter uncertainties as well as cross-correlated noise are used to describe the uncertain disturbances. Moreover, a reoptimal weighted fusion state estimation is designed to alleviate the information redundancy and maintain higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

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Section: Outputmentioning

confidence: 99%