Parameters Of Permanent Magnet Synchronous Motor Research Articles

Luenberger Position Observer Based on Deadbeat-Current Predictive Control for Sensorless PMSM

Two problems can cause control performance degradation on permanent magnet synchronous motor (PMSM) systems, namely, fluctuation of PMSM parameters and the time delay between current sampling and command value update. In order to reduce the influence of these problems, a new current-predictive control strategy is proposed in this article for medium- and high-speed PMSM. This strategy is based on the discrete mathematical model of PMSM. This new control strategy consists of two main steps: First, an integrator is applied to calculate current compensation value; second, the predictive current value is obtained through deadbeat-current predictive method. The stability of predictive control system is also proved in the article. With this deadbeat-current predictive control scheme, the real current can reach the desired value within one control-step. Based on this new current control method, Luenberger observer and phase-locked loop position tracker is applied in this article. Experimental results for 0.4 kW surface-mounted PMSM confirm the validity and excellent performance for parameters fluctuation of new current predictive control.

The Fuzzy PI Controller for PMSM’s Speed to Track the Standard Model

This paper proposes a fuzzy PI controller to control the speed of a permanent magnet synchronous motor (PMSM). The structure of the system includes the speed loop controller (SLC) and the current loop controller (CLC). The speed loop controller is the fuzzy PI and standard model (SM). The CLC includes vector control and the space vector pulse width modulation (SVPWM). It compiles two closed-loop control systems for the PMSM. This research uses a very high-speed integrated circuit hardware description language (VHDL) to implement the proposed algorithm and embed it into Matlab/Simulink for simulation. Based on the PMSM parameter, this article tests the controller’s correctness with some of the load cases by changing the combined inertia and viscous friction of rotor and load. After success in simulation, the system is tested again by experiment on the FPGA kit. The simulation and experiment results show that when the load changes, the PMSM speed is still stable. The novelty of this research is that it compares two kinds of controllers between simulation and experiment results.

Research on chaos control of permanent magnet synchronous motor based on the synthetical sliding mode control of inverse system decoupling

This article focuses on realizing the chaos control of a permanent magnet synchronous motor by combining a pseudo-linear inverse system of the permanent magnet synchronous motor and synthetical sliding mode control. First, the permanent magnet synchronous motor dimensionless nonlinear mathematical model is established, and its chaos is analyzed by the Lyapunov exponent method. The permanent magnet synchronous motor parameter range when chaos appears is obtained. Then, the inverse system decoupling method is used to analyze the reversibility of the permanent magnet synchronous motor system, and the permanent magnet synchronous motor inverse system is obtained, which is compounded with the original system into a pseudo-linear inverse system that consists of two independent subsystems, including a first-order d-axis current system and a second-order rotational speed system, to decouple the permanent magnet synchronous motor system. Third, the first-order d-axis subsystem is controlled by sliding mode control with a hyperbolic tangent function as the switching function, and the second-order speed subsystem is controlled by super-twisting sliding mode control with a hyperbolic tangent function as the switching function, which is called the synthetical sliding mode control. The permanent magnet synchronous motor pseudo-linear inverse system is controlled by using the synthetical sliding mode to realize the chaos control of the permanent magnet synchronous motor. Finally, three kinds of permanent magnet synchronous motor chaos control systems are established in MATLAB/Simulink software, and the experimental tests are implemented. The results show that the proposed permanent magnet synchronous motor chaos control system has good performance, which can effectively eliminate chattering in sliding mode control and control chaos in the permanent magnet synchronous motor system.

A Review of State-of-the-art Techniques for PMSM Parameter Identification

In this paper, a review of previous research in d- and q-axis inductance identification techniques for permanent magnet synchronous motor (PMSM) is presented. The d- and q-axis inductances have an important influence on both the transient and steady-state responses of PMSM. Therefore, their accurate information is essential not only for predicting the responses but also for designing system controllers. However, standardized procedures for the PMSM inductance identification have not yet been established. The main purpose of this paper is to provide an understanding of the various parameter identification methods. Conventional techniques are reviewed and introduced with their inherent advantages and drawbacks.

Permanent magnet synchronous motor: chaos control using single controller, synchronization and circuit implementation

The aim of this paper is to address the problem of the electronic implementation of chaos control using a single controller and synchronization of chaotic permanent magnet synchronous motor (PMSM). Firstly, different dynamical behaviors of the PMSM including steady state, periodic and chaotic behaviors are found using numerical methods such as two-dimensional largest Lyapunov exponents graph associated with two parameters of PMSM. Secondly, two simple and single controllers are designed and added to the chaotic PMSM in order to suppress chaotic behavior. The performance of the two proposed simple and single controllers is illustrated by numerical simulations. Thirdly, controllers are designed to achieve synchronization of unidirectional coupled identical chaotic PMSMs. Numerical simulations are also used to verify the effectiveness of the synchronization. Finally, the existence of chaos in PMSM and the physical feasibility of the proposed two simple and single controllers as well as the chaos synchronization are validated through the circuit implementation on OrCAD-PSpice software. The circuit implementation results comply fairly with those of the numerical simulation results and establish that the existence of chaotic behavior in the PMSM and the achievement of chaos synchronization in unidirectional coupled identical PMSMs designed and the two single controllers designed are effective and successful in suppressing chaotic behavior in PMSM.

Speed Regulation Based on Adaptive Control and RBFNN for PMSM Considering Parametric Uncertainty and Load Fluctuation

A novel speed control scheme combining adaptive speed controller and radial basis function neural network (ASC-RBFNN) is proposed for the speed regulation of permanent magnet synchronous motor (PMSM) in this paper. On one hand, in order to reduce the effect of parametric uncertainty and complicated load fluctuation on the speed control performance, an ASC is proposed. Meanwhile, the speed control system (SCS) of PMSM with the proposed ASC is asymptotically stable even though the parametric uncertainty and complicated load fluctuation exist. On the other hand, with consideration of the uncertainty of complicated load, PMSM parameters, and ASC parameters, the RBFNN is used to optimize all ASC parameters for optimal speed control performance. Finally, the performance is verified on an experiment platform. The results indicate that the SCS with the ASC-RBFNN speed control scheme is with good system stability, fast speed response, and strong anti-fluctuation performance in whole-speed range.

Adaptive Decoupling Control Using Radial Basis Function Neural Network for Permanent Magnet Synchronous Motor Considering Uncertain and Time-Varying Parameters

In this paper, a novel control scheme with respect to the adaptive decoupling controller based on radial basis function neural network (ADEC-RBFNN) is developed. On one hand, in order to improve the system performance of the torque closed-loop control system (TCLCS) of the permanent magnet synchronous motor (PMSM) with the effects of the dynamic coupling and back electromotive force (EMF), we present a novel ADEC with which the TCLCS is asymptotically stable under Lyapunov stability theory. On the other hand, considering the uncertainty and time variant of both the PMSM and ADEC parameters, the RBFNN is utilized to optimize the ADEC parameters to achieve optimal system performance. Ultimately, experimental results demonstrate that the torque and current with the proposed control scheme have the good performance of small fluctuation and fast response in the whole ranges of the speed and torque, that is to say, the system with the proposed control scheme is with the good decoupling performance.

Nonregenerative Braking of Permanent Magnet Synchronous Motor

This article proposes nonregenerative braking algorithm for the permanent magnet synchronous motor (PMSM), suitable for low-cost drive equipped with the front-end diode rectifier. The algorithm is based on the selection of braking trajectories with maximum iron and copper losses, while keeping dc-bus voltage at the acceptable level and with operational limits satisfied. The braking scheme is not calculation intensive and is not prone to PMSM parameter variations; thus, it is suitable for inexpensive microcontroller and PMSM, both native for low-cost drives. The algorithm is tested and validated under a variety of operating conditions, using a typical high-speed PMSM used in home appliances.

A Comprehensive Review of State-of-the-Art Parameter Estimation Techniques for Permanent Magnet Synchronous Motors in Wide Speed Range

Permanent magnet synchronous motor (PMSM) drive has emerged as one of the most preferred motor drives for industrial applications owing to its distinguished advantages, such as high torque density, high efficiency, and wide speed range operation. However, accurately updated knowledge about the PMSM parameters is crucial to designing a high-performance trajectory tracking controller. This article presents a state-of-the-art comprehensive review and up-to-date progress of the offline and online parameter estimation techniques of the PMSM drives. First, the problems associated with parameter estimation of the PMSM are systematically summarized to identify the parameters having fast and accurate convergence. Second, the offline parameter estimation techniques are categorized based on the frequency and time responses. Third, the recent advances and developments of the online parameter estimation techniques for PMSMs are assessed. Finally, there is a discussion of extensive industrial applications and future research trends for the parameter estimation techniques.

Research on PMSM harmonic coupling models based on magnetic co‐energy

Modelling of the permanent magnet synchronous motor (PMSM) torque ripple and PMSM current harmonics controlling technology are important branches of PMSM research. Based on the existing linear PMSM model derived from magnetic co-energy, this study considers the variation of PMSM parameters (inductance, permanent magnet flux and cogging torque) caused by magnetic saturation. Then, the harmonic coupling models including flux-current coupling model, voltage-current coupling model and torque-current coupling model are deduced. In these harmonic coupling models, the PMSM parameters no longer vary with rotor position but only with current amplitude and phase. Based on the torque-current coupling model, a novel method of obtaining the required injecting currents which could suppress torque ripple is proposed. The validity of the harmonic coupling models and the injecting current solution method is verified by finite-element method.

Adaptive gain scheduling with feedforward control system based on system model for PMSM

ABSTRACTA feedforward controller for permanent magnet synchronous motor (PMSM) has been proposed in this study, and proportional and integral gain could be self-adaptive under different operating conditions. The control structure used in the feedforward system is the same as in the feedback control system. This control structure could guarantee independence of the speed command input to output with the disturbance input to output, which makes the system have better reference trajectory tracking and disturbances rejection. In order to obtain optimal control performance when the parameters are uncertain, a gain scheduling adaptive controller is used in the feedforward system. The proposed controller has been verified by the experimental and simulation results with less steady-state error and better dynamic response than the controllers without it under the condition of external load torque disturbance and PMSM parameter uncertainties.

Robust Diagnosis Method Based on Parameter Estimation for an Interturn Short-Circuit Fault in Multipole PMSM under High-Speed Operation.

This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates the q-axis inductance (Lq) of the faulty PMSM to solve this problem. The proposed method also estimates the faulty phase and the value of G, which serves as an index of the severity of the fault. The q-axis current is used to estimate the faulty phase, the values of G and Lq. For this reason, two open-loop observers and an optimization method based on a particle-swarm are implemented. The q-axis current of a healthy PMSM is estimated by the open-loop observer with the parameters of a healthy PMSM. The Lq estimation significantly compensates for the estimation errors in high-speed operation. The experimental results demonstrate that the proposed method can estimate the faulty phase, G, and Lq besides exhibiting robustness against parameter uncertainties.

A High-performance Speed Feed-forward Controller for Permanent Magnet Synchronous Motor Based on Control System Model

This study proposes a feed-forward controller based on a control system model that can precisely track a reference trajectory by canceling out the effects of parameter uncertainties on a surface-mounted (magnets glued to the shaft surface) permanent magnet synchronous motor. Furthermore, the speed tracking control algorithm demands rapid and accurate q-axis current command, so the feed-forward system based on the control model is used to estimate it. The stability of the proposed controller is mathematically studied. The proposed control scheme is executed on a permanent magnet synchronous motor drive using a Renesas micro-control unit (RX62TADFFM, Japan). Finally, simulation and experimental results are presented to verify that the proposed controller achieves less steady-state error, better robust performance, and faster dynamic response than the proportional–integral controllers in the presence of permanent magnet synchronous motor parameter uncertainties and external load torque disturbance.

Adaptive finite-time control of chaos in permanent magnet synchronous motor with uncertain parameters

Permanent magnet synchronous motor (PMSM) exhibits chaotic behavior when its parameters are within a certain range which seriously affect the stable work of PMSM. In order to eliminate the chaos, many approaches have been proposed. Most of them considered asymptotic stability of the system, while finite-time stability makes more sense in practice. In addition, parameters of PMSM may be uncertain because of some external factors, then adaptive control is a good method to be considered. In this paper, adaptive finite-time stabilization problem is considered to eliminate the chaos in PMSM system with uncertain parameters. To show the effectiveness of the proposed method, some simulation results are provided.

Adaptive synchronization method for chaotic permanent magnet synchronous motor

This paper proposes a simple adaptive synchronization method for a chaotic permanent magnet synchronous motor (PMSM). Convergence of the closed-loop system responses is shown by using a Lyapunov function. The proposed adaptive synchronization method does not require the restrictive assumption of the complete availability of information on the PMSM parameters. Simulation results are given to verify that the proposed method can be successfully used for digital implementation and it gives an effective means for adaptive synchronization of a chaotic PMSM under model parameter variations.

Parameter Identification of PMSM Using Immune Clonal Selection Differential Evolution Algorithm

Permanent magnet synchronous motor (PMSM) models with accurate parameters are crucial to high performance PMSM control system designs. As the estimation of PMSM parameters is very difficult due to thenonlinearmodel complexity, a novel immune clonal differential evolution algorithm (ICDEA) is proposed to identify the electrical parameters of nonsalient pole PMSM. Clonal selection and receptor editing mechanism are introduced to ICDEA to increase the diversity of the population and improve searching capability. The effectiveness of the proposed identification method is verified by both simulation and experiment. The results show that the proposed algorithm has good convergence in simultaneously estimating stator resistance,dq-axis inductances, and rotor flux linkage. In addition, the convergence speed of ICDEA is compared with other differential evolution (DE) algorithms, which verifies that the ICDEA has better performances in global searching.

High-Order Terminal Sliding-Mode Observer for Parameter Estimation of a Permanent-Magnet Synchronous Motor

This paper proposes a terminal sliding-mode (TSM) observer for estimating the immeasurable mechanical parameters of permanent-magnet synchronous motors (PMSMs) used for complex mechanical systems. The observer can track the system states in finite time with high steady-state precision. A TSM control strategy is designed to guarantee the global finite-time stability of the observer and, meanwhile, to estimate the mechanical parameters of the PMSM. A novel second-order sliding-mode algorithm is designed to soften the switching control signal of the observer. The effect of the equivalent low-pass filter can be properly controlled in the algorithm based on requirements. The smooth signal of the TSM observer is directly used for the parameter estimation. The experimental results in a practical CNC machine tool are provided to demonstrate the effectiveness of the proposed method.

Application of Chaos in Permanent Magnet Synchronous Motor Optimization

Permanent magnet synchronous motor (PMSM) is a system with multi-variable, strong coupling and nonlinear. It is difficult to establish its precise mathematical model, and the parameter optimization method of PMSM control system is subject to many limitations. Aiming at the design of PID tuning of PMSM control system, a chaos optimization method based on Logistic chaotic map is proposed to avoid the complex process of PMSM modeling and parameter optimization analysis. Results have shown that this method is simple and efficient with short response time and small overshoot after the parameter optimization.

Analytical modelling and parametric sensitivity analysis for the PMSM steady‐state performance prediction

Inaccuracy in the permanent magnet synchronous motor (PMSM) steady-state performance calculation corresponds to the parameter error and model imprecision. Accurate determination of the PMSM parameters may encounter various complications because of its rotor structure and drive design. Therefore PMSM performance calculation is generally vulnerable to inaccuracy because of the parameter error. This article studies the effect of parameter error on the inaccuracy of the performance calculations. Several methods for determining the PMSM armature resistance, flux linkage constant and d- and q-axis inductances with varying level of accuracy are proposed. The presented methods are applied to a laboratory PMSM and the sensitivity of the PMSM output power to the equivalent circuit parameters is analysed based on the experimental results. In addition, this study contributes to accurate performance estimations of the PMSM by developing a precise model that incorporates the saturation saliency and core losses. The accuracy of the proposed model is compared with the conventional dq-axis model and its higher accuracy is validated through experimental results.

Adaptive sliding mode control of a chaotic nonsmooth-air-gap permanent magnet synchronous motor with uncertainties

Using the sliding mode control approach, a simple adaptive controller design method is proposed for a chaotic nonsmooth-air-gap permanent magnet synchronous motor (PMSM). The proposed method does not require the restrictive assumption that accurate information on the PMSM parameter and load torque values is available, thus it has robustness to model uncertainties. This paper analyzes the stability and convergence of the closed-loop control system, and this paper gives a discretized control algorithm for DSP implementation. Finally, this paper presents some simulation results to illuminate that the proposed method can effectively handle the controller design problem for a chaotic nonsmooth-air-gap PMSM under inaccurate information on the PMSM parameter and load torque values.