Adaptive Observer Design for Sensorless IPMSM Drives With Known Regressors Variant of Extended EMF Model

控制理论(社会学) 定子 观察员(物理) 参数统计 非线性系统 计算机科学 反电动势 控制工程 工程类 电压 数学 控制(管理) 物理 统计 电气工程 人工智能 机械工程 量子力学
作者
Qilian Lin,Ling Liu,Deliang Liang
出处
期刊:IEEE Transactions on Power Electronics [Institute of Electrical and Electronics Engineers]
卷期号:39 (1): 212-224 被引量:1
标识
DOI:10.1109/tpel.2023.3319819
摘要

This article proposes a known regressors variant of the extended electromotive force (EMF) model, enabling rigorous theoretical stability analysis about the joint estimation of position, speed, and stator resistance in the full-order observer design. According to the literature, adaptive observer designs for nonlinear systems often require the regressors to be known as well as the systems being in Brunovsky observer form. Unfortunately, none of the existing interior permanent magnet synchronous motor (IPMSM) models (i.e., the extended EMF model and the active flux model) are capable of meeting these requirements. By defining a new state variable, the extended EMF model of IPMSM can be transformed into its known regressors variant, thereby, ensuring global stability of the speed and stator resistance adaptive observer. In the new coordinate, the inclusion of stator resistance estimation leads to the overparameterization problem, thus an adaptive high-gain observer is proposed to allow certain nonlinear terms to appear in the regressors. Analyses of stability and parametric sensitivity are also presented, resulting in a robust tuning guideline for the sensorless control system. Simulations and experiments have been conducted to verify the effectiveness of the proposed adaptive observer in a sensorless IPMSM drive, and improvements have been observed in wide-speed operations and disturbance rejections.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
damian完成签到,获得积分10
刚刚
LiShin发布了新的文献求助10
刚刚
渝州人应助凤凰山采纳,获得10
1秒前
sweetbearm应助凤凰山采纳,获得10
1秒前
我是老大应助科研通管家采纳,获得10
1秒前
大个应助科研通管家采纳,获得10
1秒前
yizhiGao应助科研通管家采纳,获得10
1秒前
华仔应助科研通管家采纳,获得10
1秒前
科研通AI5应助科研通管家采纳,获得30
1秒前
顾矜应助随机起的名采纳,获得10
1秒前
NN应助科研通管家采纳,获得10
1秒前
pinging应助科研通管家采纳,获得10
2秒前
星辰大海应助科研通管家采纳,获得10
2秒前
yizhiGao应助科研通管家采纳,获得10
2秒前
小蘑菇应助科研通管家采纳,获得20
2秒前
小小旋风应助科研通管家采纳,获得10
2秒前
传奇3应助科研通管家采纳,获得10
2秒前
科研通AI5应助科研通管家采纳,获得10
2秒前
敬老院N号应助科研通管家采纳,获得30
2秒前
科研通AI5应助科研通管家采纳,获得10
2秒前
彭于晏应助科研通管家采纳,获得10
3秒前
科研通AI5应助科研通管家采纳,获得10
3秒前
yizhiGao应助科研通管家采纳,获得10
3秒前
科研通AI2S应助科研通管家采纳,获得10
3秒前
科研小白应助科研通管家采纳,获得10
3秒前
李爱国应助科研通管家采纳,获得10
3秒前
文献缺缺应助科研通管家采纳,获得10
3秒前
上官若男应助科研通管家采纳,获得10
3秒前
3秒前
调研昵称发布了新的文献求助10
3秒前
3秒前
HUYUE完成签到 ,获得积分10
4秒前
云锋完成签到,获得积分10
4秒前
奋斗战斗机完成签到,获得积分10
5秒前
SYLH应助干秋白采纳,获得10
5秒前
极意完成签到 ,获得积分10
6秒前
左友铭发布了新的文献求助10
6秒前
6秒前
6秒前
爱听歌雨真完成签到,获得积分10
7秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527884
求助须知:如何正确求助?哪些是违规求助? 3108006
关于积分的说明 9287444
捐赠科研通 2805757
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716904
科研通“疑难数据库(出版商)”最低求助积分说明 709794