结合基于 EKF 的 IPMSM 无传感器现场导向控制的反步进控制设计

Qeios Pub Date : 2024-05-09 DOI:10.32388/ixusw5
Ç. Uyulan
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引用次数: 0

摘要

集电极和无刷电子换向机器已在工业应用中得到广泛使用。在这些机器中,内部永磁同步电机(IPMSMs)因其众多优点而越来越受欢迎,包括高扭矩/电流比和扭矩/惯性比、坚固的结构、高效率和可靠性。然而,在 IPMSMs 中安装位置传感器给其应用、性能、批量生产和成本带来了挑战。因此,在驱动系统和各种应用中实施无传感器控制技术变得至关重要。本文提出了一种反步进控制方法,利用扩展卡尔曼滤波器(EKF)实现对 IPMSMs 的无速度传感器控制。第一步是在直交和正交(d-q)转子帧中建立 IPMSM 的综合非线性动力学模型,并获得相应的状态空间表示。随后,设计用于转子速度和电流跟踪的反步进控制器,以确保精确跟踪和抗干扰性能。这些控制器被集成到面向场的控制(FOC)方案中。为了应对估计 IPMSM 不可测机械参数和精确跟踪系统状态的挑战,设计了一个 EKF。该滤波器能够估算机械参数,并在有限时间内达到较高的稳态精度。通过在各种动态运行条件下(包括扭矩负载突变、指令速度变化和参数变化)进行仿真,证明了所提方法的有效性。
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Backstepping Control Design in Conjunction with an EKF-based Sensorless Field-Oriented Control of an IPMSM
The collector and brushless electronic commutation machines have gained widespread utilization in industrial applications. Among these machines, internal permanent magnet synchronous motors (IPMSMs) have become increasingly popular due to their numerous advantages, including high torque/current and torque/inertia ratios, robust construction, high efficiency, and reliability. However, the incorporation of position sensors in IPMSMs has introduced challenges concerning their application, performance, mass production, and cost. Consequently, the implementation of sensorless control techniques has become essential in drive systems and various applications. This paper proposes a backstepping control approach for achieving speed sensorless control of IPMSMs, employing an extended Kalman filter (EKF). The first step involves developing a comprehensive nonlinear dynamical model of the IPMSM in the direct and quadrature (d-q) rotor frame and obtaining its corresponding state-space representation. Subsequently, backstepping controllers for rotor speed and current tracking are designed to ensure precise tracking and anti-disturbance performance. These controllers are integrated into the field-oriented control (FOC) scheme. The Lyapunov stability theorem is employed to guarantee the asymptotic stability condition of the backstepping controller. To address the challenge of estimating immeasurable mechanical parameters of the IPMSM and accurately tracking the system states, an EKF is designed. This filter enables the estimation of mechanical parameters and achieves high steady-state precision within a finite time. The effectiveness of the proposed methodology is demonstrated through simulations conducted under various dynamic operating conditions, including sudden torque load changes, command speed changes, and parameter variations.
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