梯度提升最小二乘支持向量回归的压电执行器磁滞特性建模  

Hysteresis characteristics modeling of piezoelectric actuator by gradient boosting least-squares support vector regression

作　　者：王建成 李强亚 刘涛[1] 谭永红[2] 阎帅 WANG Jian-cheng;LI Qiang-ya;LIU Tao;TAN Yong-hong;YAN Shuai(School of Control Science and Engineering,Dalian University of Technology,Dalian Liaoning 116024,China;College of Mechanical and Electronic Engineering,Shanghai Normal University,Shanghai 201814,China)

机构地区：[1]大连理工大学控制科学与工程学院,辽宁大连116024 [2]上海师范大学信息与机电工程学院,上海201814

出　　处：《控制理论与应用》2024年第9期1692-1697,共6页Control Theory & Applications

基　　金：国家自然科学基金项目(62327807,62361136585);教育部重点基地平台科研专题项目(DUT21LAB113)资助.

摘　　要：针对用于精密运动定位的压电执行器具有磁滞效应的问题,本文提出一种基于梯度提升最小二乘支持向量回归(GB-LSSVR)的建模方法.首先,通过引入磁滞算子构造拓展的输入空间,将磁滞的多值映射转换为一对一映射.然后,建立基于GB-LSSVR的磁滞模型,设计可保证收敛粒子群算法(GCPSO)对GB-LSSVR模型参数进行优化.最后,将所提出方法用于实际预测一个压电执行器的位移.结果表明,该方法相对于经典的最小二乘支持向量回归(LSSVR)和截断最小二乘支持向量回归(T-LSSVR)算法,能得到更加准确的结果.Concerning the problem of hysteresis effect related to piezoelectric actuators used for precise motion positioning,a modeling method is proposed based on the gradient boosting least-squares support vector regression(GBLSSVR).Firstly,an expanded input space is constructed by introducing a hysteretic operator,such that the multi-valued mapping of hysteresis is transformed into a one-to-one mapping.Then the hysteresis model is established based on the GB-LSSVR,of which the parameters are optimized by the guaranteed convergence particle swarm optimization(GCPSO)algorithm.Finally,the proposed method is applied to practically predict the displacement of a piezoelectric actuator.The results show that the proposed method could obtain more accurate result compared to the classical algorithms of least-squares support vector regression and truncated least-squares support vector regression.

关 键 词：压电执行器 磁滞效应 磁滞算子 最小二乘支持向量机 可保证收敛粒子群算法 梯度提升 

分 类 号：TN384[电子电信—物理电子学] TP18[自动化与计算机技术—控制理论与控制工程]