文献类型：期刊文献

英文题名：PSO-Assisted Memory Sliding Mode Observer for High-order Systems

作者：Li, Xikang[1]; Xu, Jing[1]; Niu, Yugang[1]

机构：[1] Ministry of Education, East China University of Science and Technology, Key Laboratory of Energy and Chemical Process Intelligent Manufacturing, China

年份：2022

卷号：2022-July

起止页码：692

外文期刊名：Chinese Control Conference, CCC

收录：EI(收录号：20224413019662)

基金：This work is partially supported by the National Natural Science Foundation of China (62173141, 62073139), and the Natural Science Foundation of Shanghai (22ZR1417900).

语种：英文

外文关键词：DC motors - Decay (organic) - Sliding mode control - System stability - Uncertainty analysis

摘要：This paper designs a novel memory sliding mode observer to estimate system states in the presence of matched uncertainty. First, the error system is obtained and estimated by static differential estimation theory. Based on the equivalent control method, the equivalent control law is obtained to ensure the closed-loop exponential stability and the Lyapunov theory is used to realize robust exact estimation of the system state. Second, the parameter optimization via particle swarm optimization is chosen between three competing design objectives: the system decay rate, the control efforts, and the attenuation of high-frequency measurement noise. Finally, the effectiveness of the proposed memory sliding mode observer is verified by a numerical simulation example on a DC motor system. ? 2022 Technical Committee on Control Theory, Chinese Association of Automation.