Deep-sea vessel dynamic positioning oriented high-precision real-time state estimation method and system

Abstract

The invention relates to a deep-sea vessel dynamic positioning oriented high-precision real-time state estimation method and system. The method includes: separating a high-frequency signal caused by a first-order wave force from a low-frequency vessel motion signal so as to obtain a high-frequency motion component and a low-frequency motion component; in a marginalized particle filter frame, subjecting both the high-frequency motion component the low-frequency motion component to parameter estimation and state estimation; using results of the parameter estimation and state estimation as input of next-cycle parameter estimation and state estimation, and repeating the steps until the end. The deep-sea vessel dynamic positioning oriented high-precision real-time state estimation method and system has the advantages that the difference between high-frequency linear motion and low-frequency linear motion is fully considered, the nose parameter estimation method applicable to both high-frequency and low-frequency motions is provided, the state estimation method based on marginalized particle filter and oriented towards vessel dynamic positioning is therefore provided, and state estimation precision increase and timeliness are balanced.

Description

technical field [0001] The invention belongs to the field of ships and ocean engineering, and in particular relates to a high-precision real-time state estimation method and system for dynamic positioning of deep-sea ships. Background technique [0002] Countries in the world today are facing serious energy shortages, and the ocean is rich in resources. Therefore, countries around the world are competing to shift their strategic focus to the ocean field, investing a lot of manpower and material resources in marine geological surveys, oil and gas exploration, aquatic fishing, Research work such as marine surveys and underwater archaeology. The 18th National Congress of the Communist Party of my country held in our country also raised the construction of a maritime power to the national strategic level. The development of advanced marine technology and equipment plays an extremely important role in the development of marine resources and the protection of national marine righ...

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Problems solved by technology

[0004] However, the state estimation filter used in the existing ship dynamic positioning system has the following problems: the classical Kalman filter is only suitable for the state estimation of the linear system; although the extended Kalman filter can be applied to the nonlinear system, its There is a large estimation error, so the accuracy of state estimation cannot meet the needs of practical applications; although the nonlinear passive observer overcomes the shortcomings of the extended Kalman filter and is successfully applied to the state estimation of nonlinear systems, but , under normal circumstances, when the noise parameters introduced by the first-order wave force cannot be accurately estimated, there will be a large error in the estimation of the wave frequency, which will cause the filtering accuracy to decrease or even diverge

Due to the complexity of the low-frequency nonlinear motion model, the existing algorithms focus on estimating the parameters in the high-frequency linear motion model. As far as the single parameter estimation algorithm is concerned, the estimation accuracy based on the prediction error estimation method is not high, and the algorithm is prone to divergence. The problem; the method based on maximum likelihood estimation is difficult to deal with the problem of parameter estimation with missing data

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