扭矩
控制理论(社会学)
惯性
齿槽效应转矩
鉴定(生物学)
直接转矩控制
计算机科学
控制工程
工程类
物理
感应电动机
人工智能
电压
控制(管理)
电气工程
生物
热力学
经典力学
植物
作者
He Chang,Shaowu Lu,Bao Song,Jun Yang
标识
DOI:10.1109/tie.2024.3456901
摘要
Committed to the fact that the cogging torque of permanent magnet synchronous motors (PMSMs) under low-speed operation severely aggravates the speed ripple as well as the identification performance of inertia, this article puts forward an interconnection network (IN) using three extended sliding-mode observers (ESMOs) for the precise identification of both inertia and cogging torque. Difference from existing parallel observers, an adaptive-reaching gain (ARG) for each observer is designed to fully exploit the identification performance while minimizing undesirable low sliding-mode tremors. Moreover, a constraint criterion is adopted to limit the ARG for the IN’s stability. By constructing an auxiliary function, more notably, the first ESMO in this IN is capable of identifying the cogging torque’s eigenvalue online, which allows its mathematical model to be, thoroughly, linearized. Meanwhile, the second dual-state ESMO to observe its model parameters, where a tradeoff activator is exploited to suppress the coupling effect caused by estimation errors between the dual-state items, is combined for facilitating the accurate cogging torque. Finally, a stable inertia observed by the third ESMO is guaranteed via this IN. The advantages of the proposed scheme are verified by experimental results.
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