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Recursive parameter identification for second-order K-T equations of marine robot in horizontal motion


Affiliations
1 School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030, China
2 Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, China
3 School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030,, China

In this paper, a dedicated recursive least squares algorithm combining forgetting and weighted factors (FW-RLS) is proposed to identify parameters for the second-order K-T equation of marine robot in horizontal motion. First, the Abkowitz model in horizontal motion is converted into an equivalent second-order K-T equation to reduce the number of identification parameters. Second, a dedicated FW-RLS algorithm based on the equivalent second-order K-T equation is proposed. Finally, the superiority of the FW-RLS algorithm is verified by comparative numerical simulations, which show the FW-RLS algorithm has the online identification capability, higher identification accuracy, and faster convergence rate compared with the traditional batch least squares method
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  • Recursive parameter identification for second-order K-T equations of marine robot in horizontal motion

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Authors

Y M Zhong
School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030, China
C Y Yu
School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030, China
C H Liu
School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030, China
T M Liu
Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, China
R Wang
School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030,, China
L Lian
School of Oceanography, Shanghai Jiao Tong University, Shanghai – 200 030,, China

Abstract


In this paper, a dedicated recursive least squares algorithm combining forgetting and weighted factors (FW-RLS) is proposed to identify parameters for the second-order K-T equation of marine robot in horizontal motion. First, the Abkowitz model in horizontal motion is converted into an equivalent second-order K-T equation to reduce the number of identification parameters. Second, a dedicated FW-RLS algorithm based on the equivalent second-order K-T equation is proposed. Finally, the superiority of the FW-RLS algorithm is verified by comparative numerical simulations, which show the FW-RLS algorithm has the online identification capability, higher identification accuracy, and faster convergence rate compared with the traditional batch least squares method