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

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.