现代电子技术2024，Vol.47Issue(20)：165-169,5.DOI:10.16652/j.issn.1004-373x.2024.20.026
非线性Thau观测下的水下机器人定速推进故障识别
Fault identification of constant speed propulsion of underwater vehicle under nonlinear Thau observation
摘要
Abstract
The complex influence of hydrodynamics such as water flow,turbulence and eddy current on the underwater robot in the water has a nonlinear effect on the propulsion system,which makes the working state change slightly,and it is difficult to accurately estimate the operating state and increase the difficulty of fault identification.Therefore,a fault identification method for constant speed propulsion of underwater vehicle under nonlinear Thau observation is proposed.The lossless Kalman filter is used to estimate the state quantity of constant speed propeller of underwater vehicle.Based on the nonlinear Thau observation algorithm and state estimation results,a nonlinear Thau observer is established to identify the faults of constant speed propulsion.The bounded nonlinear uncertainty disturbance in the nonlinear Thau observer is approximated by means of fuzzy neural network to improve the fault identification accuracy.The experimental results show that the proposed method can effectively estimate the state quantity of the constant speed propeller of underwater vehicle,and approximate the bounded nonlinear uncertainty disturbance of the nonlinear Thau observer.This method can effectively identify the fault of constant speed propulsion,and the fault identification accuracy is high.关键词
非线性/Thau观测/水下机器人/定速推进/故障识别/无损卡尔曼滤波/模糊神经网络Key words
nonlinearity/Thau observation/underwater wehicle/constant speed propulsion/fault identification/unscented Kalman filter/fuzzy neural network分类
信息技术与安全科学引用本文复制引用
张博憧,韩世迁,王萍萍..非线性Thau观测下的水下机器人定速推进故障识别[J].现代电子技术,2024,47(20):165-169,5.基金项目
国家自然科学基金面上项目(62175453) （62175453）
