PARAMETRIC IDENTIFICATION AND SENSITIVITY ANALYSIS FOR AUTONOMOUS UNDERWATER VEHICLES IN DIVING PLANE  

作　　者：XU Feng ZOU Zao-jian YIN Jian-chuan CAO Jian 

机构地区：[1]School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240,China [2]School of Naval Architecture, Ocean and Civil Engineering and State Key Laboratory of Ocean Engineering,Shanghai Jiao Tong University, Shanghai 200240, China [3]College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China

出　　处：《Journal of Hydrodynamics》2012年第5期744-751,共8页水动力学研究与进展B辑（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.50979060,51079031)

摘　　要：The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles （AUV）, maneuvering motion in the diving plane determines its difficulty in parametric identification. The motion parameters in diving plane are obtained by executing the Zigzag-like motion based on a mathematical model of maneuvering motion. A separate identification method is put forward for parametric identification by investigating the motion equations. Support vector machine is proposed to estimate the hydrodynamic derivatives by analyzing the data of surge, heave and pitch motions. Compared with the standard coefficients, the identified parameters show the validation of the proposed identification method. Sensitivity analysis based on numerical simulation demonstrates that poor sensitive derivative gives bad estimation results. Finally the motion simulation is implemented based on the dominant sensitive derivatives to verify the reconstructed model.The inherent strongly nonlinear and coupling performance of the Autonomous Underwater Vehicles （AUV）, maneuvering motion in the diving plane determines its difficulty in parametric identification. The motion parameters in diving plane are obtained by executing the Zigzag-like motion based on a mathematical model of maneuvering motion. A separate identification method is put forward for parametric identification by investigating the motion equations. Support vector machine is proposed to estimate the hydrodynamic derivatives by analyzing the data of surge, heave and pitch motions. Compared with the standard coefficients, the identified parameters show the validation of the proposed identification method. Sensitivity analysis based on numerical simulation demonstrates that poor sensitive derivative gives bad estimation results. Finally the motion simulation is implemented based on the dominant sensitive derivatives to verify the reconstructed model.

关 键 词：parametric identification Autonomous Underwater Vehicles （AUVs） support vector machine sensitivity analysis 

分 类 号：TP242.3[自动化与计算机技术—检测技术与自动化装置] P641.2[自动化与计算机技术—控制科学与工程]