Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

Shao, Meng; Deng, Yongting; Li, Hongwen; Liu, Jing; Fei, Qiang

doi:10.3390/en12101857

Cited by 18 publications

(9 citation statements)

References 35 publications

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“…It is obvious from the Equations (6) and (7), that the linear transfer functions from u 0 (s) to i 0 (s), from u q (s) to i q (s) and u d (s) to i d (s) are equal and are expressed as follows:…”

Section: Mathematical Model Of a Spmsm With An Ideal Pwm Invertermentioning

confidence: 99%

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Modified Technique of Parameter Identification of a Permanent Magnet Synchronous Motor with PWM Inverter in the Presence of Dead-Time Effect and Measurement Noise

et al. 2019

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The paper considers the problem of parameter identification of the surface mounted permanent magnet synchronous motor (SPMSM) with pulse width modulated (PWM) inverter in the presence of dead time of power switches and other nonlinear distortions. Parameter identification of the SPMSM is required for the tuning of the torque control loop, because in some cases, the exact values of phase resistances and inductances are not known. In the absence of nonlinear disturbances, the problem of SPMSM parameters estimation is not difficult. The influence of the dead-time effect, back electromotive force and measurements noise introduces distortions in experimental output data sets, which leads to incorrect parameter estimation. Thus, there is a need to develop new designs of identification experiments and methods of processing of the experimental data. A detailed mathematical model of SPMSM with a PWM inverter in the presence of dead-time effect is considered in the paper. The negative influence of the dead-time effect on the results of parameter estimation is shown. A modified technique of parameter identification of SPMSM based on the estimation of frequency response function is proposed. The applied design of identification experiments, the type of excitation input signal, and methods of data processing allow us to minimize the influence of nonlinear disturbances and to reduce the variance of estimation of frequency response function. These features provide a high performance of SPMSM parameters estimation.

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Section: Mathematical Model Of a Spmsm With An Ideal Pwm Invertermentioning

confidence: 99%

“…The advantages and disadvantages of using the PMSM in such systems are described in many scientific works, for example [1][2][3][4][5]. Effective torque control of the PMSM under different operating conditions remains an important scientific task [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Modified Technique of Parameter Identification of a Permanent Magnet Synchronous Motor with PWM Inverter in the Presence of Dead-Time Effect and Measurement Noise

et al. 2019

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“…For instance, in [33], a compound terminal SMO is applied to estimate the parameter disturbances in real time. In [34], an extended sliding mode disturbance observer is designed to observe the system disturbances caused by mismatched parameters and external load, and provide a feed-forward compensation to the controller. However, the introduction of disturbance observers complicates the control system.…”

Section: Introductionmentioning

confidence: 99%

An Improved Super-Twisting High-Order Sliding Mode Observer for Sensorless Control of Permanent Magnet Synchronous Motor

Zhao

Wang

2021

Energies

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This article presents an improved super-twisting high-order sliding mode observer for permanent magnet synchronous motors to achieve high-performance sensorless control. The proposed observer is able to simultaneously estimate rotor position and speed, as well as track parameter disturbances online. Then, according to the back-EMF model, the sensorless observer is further constructed to improve the estimation effect. The estimated rotor position and speed are used to replace the actual values detected by the sensor, and the estimated parameter disturbances are considered as feedback values to compensate the command voltage. In this way, not only is the estimation accuracy improved, but the robustness against uncertainties is also enhanced. Simulation and experimental results show that the proposed observer can effectively track the rotor position and speed and obtain good dynamic and steady-state performance.

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“…Other methods exist in the literature which are based on neural networks [3][4][5][6]. Identification methods based on nonlinear observers/filters such as methods based on the extended Kalman filter [7], high-gain observers [8], and observers based on sliding modes [9][10][11][12] have also been proposed. The drawback of these last ones is that they depend on a priori knowledge of the modeled system, which can sometimes be quite complex and inaccurate.…”

Section: Introductionmentioning

confidence: 99%

Software Sensor to Enhance Online Parametric Identification for Nonlinear Closed-Loop Systems for Robotic Applications

Sidhom

Chihi

Kamavuako

2021

Sensors

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This paper proposes an online direct closed-loop identification method based on a new dynamic sliding mode technique for robotic applications. The estimated parameters are obtained by minimizing the prediction error with respect to the vector of unknown parameters. The estimation step requires knowledge of the actual input and output of the system, as well as the successive estimate of the output derivatives. Therefore, a special robust differentiator based on higher-order sliding modes with a dynamic gain is defined. A proof of convergence is given for the robust differentiator. The dynamic parameters are estimated using the recursive least squares algorithm by the solution of a system model that is obtained from sampled positions along the closed-loop trajectory. An experimental validation is given for a 2 Degrees Of Freedom (2-DOF) robot manipulator, where direct and cross-validations are carried out. A comparative analysis is detailed to evaluate the algorithm’s effectiveness and reliability. Its performance is demonstrated by a better-quality torque prediction compared to other differentiators recently proposed in the literature. The experimental results highlight that the differentiator design strongly influences the online parametric identification and, thus, the prediction of system input variables.

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Sliding Mode Observer-Based Parameter Identification and Disturbance Compensation for Optimizing the Mode Predictive Control of PMSM

Cited by 18 publications

References 35 publications

Modified Technique of Parameter Identification of a Permanent Magnet Synchronous Motor with PWM Inverter in the Presence of Dead-Time Effect and Measurement Noise

Modified Technique of Parameter Identification of a Permanent Magnet Synchronous Motor with PWM Inverter in the Presence of Dead-Time Effect and Measurement Noise

An Improved Super-Twisting High-Order Sliding Mode Observer for Sensorless Control of Permanent Magnet Synchronous Motor

Software Sensor to Enhance Online Parametric Identification for Nonlinear Closed-Loop Systems for Robotic Applications

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