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Yong Xiong1,2,3,Xianfei Wang1,Siwen Zhou1.[en_title][J].Control Theory and Technology,2024,22(2):292~314.[Copy]
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Online interactive identificationmethod based on ESO disturbance estimation for motion model of double propeller propulsion unmanned surface vehicle
YongXiong1,2,3,XianfeiWang1,SiwenZhou1
0
(1 School of Navigation, Wuhan University of Technology, Wuhan 430063, Hubei, China 2 National Engineering Research Center for Water Transport Safety, Wuhan 430063, Hubei, China 3 Hubei Inland Technology Key Laboratory, Wuhan 430063, Hubei, China)
摘要:
In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.
关键词:  Identification of parameters · Ship motion model · Extended state observer · Multinomial innovation least squares · Interactive identification
DOI:https://doi.org/10.1007/s11768-024-00201-1
基金项目:This work was supported by the National Natural Science Foundation of China (No. 52271367).
Online interactive identificationmethod based on ESO disturbance estimation for motion model of double propeller propulsion unmanned surface vehicle
Yong Xiong1,2,3,Xianfei Wang1,Siwen Zhou1
(1 School of Navigation, Wuhan University of Technology, Wuhan 430063, Hubei, China 2 National Engineering Research Center for Water Transport Safety, Wuhan 430063, Hubei, China 3 Hubei Inland Technology Key Laboratory, Wuhan 430063, Hubei, China)
Abstract:
In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.
Key words:  Identification of parameters · Ship motion model · Extended state observer · Multinomial innovation least squares · Interactive identification