System Identification of Underwater Vehicles with ML Algorithm

Jian Guo Wang; Gang Yi Hu; Chun Meng Jiang

doi:10.4028/www.scientific.net/AMM.455.366

Paper Titles

A Human Target Detection and Tracking Method Based on Adaptive Difference and GVF-Snake Algorithm
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Application of Low-Voltage Carrier Meter Reading System in the Electricity Network Management
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Dimensional Synthesis of 3PRS Parallel Mechanism Based on a Dimensionally Homogeneous Analytical Jacobian
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Inverse Dynamics Formulation and Analysis of a Parallel Manipulator with 3DOFs Based on the Virtual Work Principle
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System Identification of Underwater Vehicles with ML Algorithm
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A Design of Short Range Wireless Communication Module Based on nRF24L01
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Research of Gear Shift Control Technology for a New 8-Step Speed Automatic Transmission
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Numerical Simulation of Synthetic Jet Actuator and its Controlling Effect on the S-Inlet
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The Robot Wrist Sensor Dynamic Mode Building Method Based on Genetic Wavelet Neural Networks
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 455System Identification of Underwater Vehicles with...

System Identification of Underwater Vehicles with ML Algorithm

Abstract:

Maximum-likelihood (ML) and its relaxation algorithm are discussed which are used to identify the mathematics model of an Underwater Vehicle (UV). With trial data of zigzag tests, the hydrodynamic derivatives of the UV were estimated, and the better astringency of the relaxation algorithm can be acquired from the contrast between the two methods. A simulation environment based on these parameters is established to verify the validity and effect of these methods. The result shows the model is credible and the methods are very useful for the research of maneuverability and intelligent control of underwater vehicles.