期刊
IEEE JOURNAL OF OCEANIC ENGINEERING
卷 44, 期 3, 页码 642-663出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JOE.2018.2827678
关键词
Online system identification (SI); recursive least squares (RLS); underwater vehicles
This paper presents an unsupervised strategy for online system identification of underwater robotic vehicles. The proposed method consists of four operating modules, namely the state estimation module, the collision avoidance module, the excitation module, and the parameter estimation module, that collaborate online in a closed-loop architecture. The excitation inputs are formulated online, based on the convergence achieved for each actuated degree of freedom, thus speeding up the identification process while concurrently evading overfitting. Additionally, the proposed algorithm guarantees safe operation by avoiding collisions with the workspace boundaries; hence, no human supervision is required during the identification procedure. Moreover, the overall scheme is of low complexity and can be easily integrated into the realtime embedded system framework of underwater robotic vehicles. Finally, the efficacy of the proposed strategy was experimentally verified via an online system identification of a small underwater robotic vehicle, and the accuracy of the estimated parameters was further experimentally evaluated via a trajectory tracking task, by comparing the performance of a PID control scheme that employed feedforward compensation of the identified dynamics, with the corresponding performance of a conventional model-free PID control scheme.
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