文献类型：期刊文献

英文题名：H∞ memory observer design for vehicle suspension state estimation and unknown road reconstruction

作者：Wang, Gang Chadli, Mohammed Mammar, Said

第一作者：王刚

机构：[1] School of Mechanical Engineering, Guizhou Institute of Technology, Guiyang, China; [2] University Paris-Saclay, Univ.Evry, IBISC, Evry, France

第一机构：贵州理工学院机械工程学院

年份：2020

起止页码：479-483

外文期刊名：2020 28th Mediterranean Conference on Control and Automation, MED 2020

收录：EI(收录号：20204109327877)

语种：英文

外文关键词：Roads and streets - Automobile suspensions

摘要：This brief is concerned with the state estimation problem for a vehicle suspension subjected to unknown road input. Limited by installation space and number of sensors, the measurable states are limited. To estimate the entire suspension states and road profile simultaneously, an H∞ memory observer (HMO) is developed. Unlike the traditional unknown input observer (UIO) designed to the suspension system, the proposed HMO takes advantage of the memory outputs. Disturbance decoupling and H∞ attenuation techniques are used in the design. Furthermore, a sufficient condition based on LMI framework is provided to find the observer gains. The simulation results show that the HMO is efficient and the estimated values are very close to the real ones. ? 2020 IEEE.