典型文献
Submarine Multi-Model Switching Control Under Full Working Condition Based on Machine Learning
文献摘要：
A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degreee-of-freedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.
文献关键词：
中图分类号：
作者姓名：
LIANG Liang;SHI Ying;MOU Junmin
作者机构：
School of Automation,Wuhan University of Technology,Wuhan 430070,China;Hubei Key Laboratory of Inland Shipping Technology;School of Navigation, Wuhan University of Technology, Wuhan 430063, China
文献出处：
引用格式：
[1]LIANG Liang;SHI Ying;MOU Junmin-.Submarine Multi-Model Switching Control Under Full Working Condition Based on Machine Learning)[J].上海交通大学学报（英文版）,2022(03):402-410
A类：
degreee,FPID
B类：
Submarine,Multi,Model,Switching,Control,Under,Full,Working,Condition,Based,Machine,Learning,continuous,submarine,depth,strategy,multi,model,machine,learning,switching,method,under,full,working,proposed,this,paper,motion,six,freedom,first,built,decoupled,according,force,analysis,set,corresponding,precise,then,optimized,different,conditions,studied,using,algorithm,simulation,experiments,indicate,that,comprised,proportional,integral,derivative,fuzzy,predictive,controllers,support,vector,can,realize,showing,good,performance,compared,single
AB值：
0.572924
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