Load Torque and Moment of Inertia Identification for Permanent Magnet Synchronous Motor Drives Based on Sliding Mode Observer

Lian, Chuanqiang; Xiao, Fei; Gao, Shan; Liu, Jilong

doi:10.1109/tpel.2018.2870078

Cited by 88 publications

(40 citation statements)

References 23 publications

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“…A secondorder terminal sliding-mode observer (SMO) is proposed to estimate mechanical parameters, such as , and , and achieves fast convergence in finite time [41]. In [42], a SMO based observer and two-moment of inertia estimation methods are developed to estimate , and , where the estimation error of load torque due to mismatches of the mechanical parameters are considered. To identify the load torque under variable-speed or variable-load servo drive system, an improved adaptive SMO is proposed in [43].…”

Section: A Determination Of Mechanical Parametersmentioning

confidence: 99%

Online Parameter Estimation for Permanent Magnet Synchronous Machines: An Overview

2021

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Online parameter estimation of permanent magnet synchronous machines is critical for improving their control performance and operational reliability. This paper provides an overview of the recent achievements of online parameter estimation of PMSMs with examples. The critical issues in parameter estimation are firstly analysed, especially the rank-deficient issue and inverter nonlinearities. Then, the stateof-the-art online parameter estimation modelling techniques are reviewed and assessed. Finally, some typical applications and examples are outlined, e.g. estimation of mechanical parameters, improvement of sensored and sensorless control performance, thermal condition monitoring, and fault diagnosis, together with future research trends.INDEX TERMS Condition monitoring, control performance, electrical parameter, fault diagnosis, mechanical parameter, online parameter estimation, permanent magnet synchronous machine, sensorless control.

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Section: A Determination Of Mechanical Parametersmentioning

confidence: 99%

Online Parameter Estimation for Permanent Magnet Synchronous Machines: An Overview

2021

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“…These methods are commonly used in middle and high speed control occasions, such as Nonlinear Observers [6,7], Model Reference Adaptive Algorithms [8,9], Extended Kalman Filter Algorithm [10,11], Sliding Mode Observer Algorithm [12,13]. Compared with above methods, Sliding Mode Observer (SMO) is a nonlinear and a variable structure control principle discontinuous control strategy, and it has been concerned by an increasing number of researchers because of its strong robustness to external disturbance, low sensitivity to parameters changes and good dynamic performance [14]. Due to the discontinuity of traditional SMO, a lot of noise signals are introduced into the observed back-EMF, which affects the performance of the observer [15].…”

Section: Introductionmentioning

confidence: 99%

Design of Improved Integral Sliding Mode Observer for Surface-Mounted Permanent Magnet Synchronous Motor

Liu¹,

Zhang²,

Cheng³

et al. 2021

Preprint

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An improved integral sliding mode observer (SMO) is proposed for the double closed-loop control system of Surface-Mounted Permanent Magnet Synchronous Motor(SPMSM) in this paper. By observing the stator current, the extended back Electromotive Force(back-EMF)of the motor is estimated, and the position and angle of the rotor are obtained by using the Phase-Locked Loop (PLL) structure. The improved integrated SMO control system not only ensures the system to converge to the equilibrium point in finite time, but also reduces the steady-state error. A new exponential reaching law is also designed in which the sgn (s) of the constant velocity term is replaced by the sigmoid (s). For improving the reaching speed, the gain adaptive function is added to the exponential term of the approaching law to make its coefficient change with the system state. Simulation results compared with the traditional SMO show that the control system based on the improved SMO can reduce observation error, enhance robustness, and suppress chattering phenomenon.

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“…In Song and Sun (2017), a combined method consisting of disturbance observer and inertia identification is employed to improving the anti-disturbance performance of PMSM when the load varies slightly. A load torque observer and two moment of inertia identification methods is introduced for PM synchronous motor drive system in Lian et al (2019). Simulation and experimental results show that the proposed inertia estimation methods have improved estimation accuracy and fast convergence speed compared with the conventional motor driven methods.…”

Section: Introductionmentioning

confidence: 99%

Model-based model predictive control for a direct-driven permanent magnet synchronous generator with internal and external disturbances

Yongwei

et al. 2019

Transactions of the Institute of Measurement and Control

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This paper deals with the critical issue in a direct-driven permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS): the rejection of internal and external disturbances, including the uncertainties of external environment, rapid wind speed changes in the original parameters of the generator caused by mutative operating conditions. To track the maximum power, a maximum power point tracking strategy based on model predictive controller (MPC) is proposed with extended state observer (ESO) to attenuate the disturbances and uncertainties. In real application, system inertia and the system parameters vary in a wide range with variations of wind speeds and disturbances, which substantially degrade the maximum power tracking performance of wind turbine. The MPC design should incorporate the available model information into the ESO to improve the control efficiency. Based on this principle, a model-based MPC with ESO control structure is proposed in this paper. Simulation study is conducted to evaluate the performance of the proposed control strategy. It is shown that the effect of internal and external disturbances is compensated in a more effective way compared with the ESO-based MPC approach and traditional proportional integral differential (PID) control method.

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Load Torque and Moment of Inertia Identification for Permanent Magnet Synchronous Motor Drives Based on Sliding Mode Observer

Cited by 88 publications

References 23 publications

Online Parameter Estimation for Permanent Magnet Synchronous Machines: An Overview

Online Parameter Estimation for Permanent Magnet Synchronous Machines: An Overview

Design of Improved Integral Sliding Mode Observer for Surface-Mounted Permanent Magnet Synchronous Motor

Model-based model predictive control for a direct-driven permanent magnet synchronous generator with internal and external disturbances

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