Active learning-based metamodeling for hybrid uncertainty quantification of hydro-mechatronic-control systems:A case study of EHA systems

作     者：Muchen WU Hao CHEN Minghao TAI Tangfan XIAHOU Zehua GE Zhenyu LIU Bing CHU Zhongrui ZHAO Yu LIU 

作者机构：AVIC Shenyang Aircraft Design and Research InstituteShenyang 110035China School of Mechanical and Electrical EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 611731China Center for System Reliability and SafetyUniversity of Electronic Science and Technology of ChinaChengdu 611731China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2024年第37卷第12期

页      面：12-30页

核心收录：

学科分类：082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：the National Natural Science Foundation of China(Nos.72301057,72271044,72331002,and 52305010) the Sichuan Science and Technology Program,China(No.2023YFG0157) 

主　　题：Electro-Hydrostatic Actuator(EHA) Hybrid uncertainty Metamodeling Optimized Max-Minimize Distance(OMMD) Hydro-mechatronic-control systems 

摘      要：The Electro-Hydrostatic Actuator(EHA)is a typical hydro-mechatronic control *** to the limited accuracy of measurement,inadequate knowledge,and vague judgments,hybrid uncertainties,including aleatory and epistemic uncertainties,inevitably exist in the performance assessment of EHA *** methods ignored the hybrid uncertainties which can hardly obtain a satisfactory result while wasting a lot of time on the experimental *** overcome this drawback,a metamodeling method for hybrid uncertainty propagation of EHA systems is developed via an active learning Gaussian Process(GP)*** proposed method is bifurcated into three pillars:(A)Initializing the GP model and generating the optimum candidate sampling set by an Optimized Max-Minimize Distance(OMMD)algorithm,which aims to maximize the minimum distance between the added samples and original samples,(B)maximizing the learning function and generating new samples by a developed farthest or nearest judgment strategy,while updating the original GP model,and(C)judging the convergence by three uncertainty metrics,i.e.,the area metric,maximum variance metric,and the mean value metric.A numerical example is exemplified to evaluate the effectiveness and efficiency of the proposed ***,the EHA system of aircrafts is examined to show the application of the proposed method for high-dimensional *** effects of the uncertainties in the Proportional-Integral-Differential(PID)of the EHA system are also examined.