Force ripples such as slot force, end force and normal force are key factor which affect the properties of permanent magnet linear synchronous motor(PMLSM). In order to obtain a high speed and high precision direct driver system, a finite element model of PMLSM is created and the slot force is analysed firstly. The slot force curve is fitted and obtained using Fourier series secondly. Then, a current predictive model is designed to compensate the thrust ripple due to the slot force. Furthermore, a disturbance observer is designed to compensate the thrust ripples due to other elements. Experiments demonstrate that the compensating control theory and analysis method are effective, and the obtained formula can be utilized to compensate thrust ripples in practical application and improve the motion performance of PMLSM.

Force ripples such as slot force, end force and normal force are key factor which affect the properties of permanent magnet linear synchronous motor(PMLSM). In order to obtain a high speed and high precision direct driver system, a finite element model of PMLSM is created and the slot force is analysed firstly. The slot force curve is fitted and obtained using Fourier series secondly. Then, a current predictive model is designed to compensate the thrust ripple due to the slot force. Furthermore, a disturbance observer is designed to compensate the thrust ripples due to other elements. Experiments demonstrate that the compensating control theory and analysis method are effective, and the obtained formula can be utilized to compensate thrust ripples in practical application and improve the motion performance of PMLSM.

In vector control system of PMSM, current controller performance will decline significantly because of changes in motor parameters, an on-line adaptive control of PMSM current-loop based on parameter identification is proposed. First stator resistance and permanent magnet flux linkage are identified using recursive least squares method with forgetting factor, and then d-q axis inductance are estimated using the same method base on the previous step, finally the PI parameters in real-time operating conditions could be obtained. Experimental results show that PI parameters can effectively adapt to change in working conditions and quickly achieve precise control of current.

In vector control system of PMSM, current controller performance will decline significantly because of changes in motor parameters, an on-line adaptive control of PMSM current-loop based on parameter identification is proposed. First stator resistance and permanent magnet flux linkage are identified using recursive least squares method with forgetting factor, and then d-q axis inductance are estimated using the same method base on the previous step, finally the PI parameters in real-time operating conditions could be obtained. Experimental results show that PI parameters can effectively adapt to change in working conditions and quickly achieve precise control of current.

The high-performance Direct Torque Control (DTC) requires accurate knowledge of flux and speed information. Furthermore, the elimination of sensors leads to reduced overall cost and size of the electric drive system and subsequently improving its reliability. This paper proposes an effective sensorless direct torque control scheme for induction motor drive. The proposed scheme consists of enhancing the decoupling structure and variable estimation as well. Therefore, an enhanced direct flux and torque control based on feedback linearization is implemented in one hand. This allows obtaining a linear decoupled control together with minimized flux and torque ripples. In another hand, a combined sliding mode observer and model reference adaptive system is associated with the control scheme as sensorless algorithms for rotor speed and flux estimation. This conjunction is intended to enhance the sliding mode observer performances especially at low speed operations and reduce its sensitivity to noise and system uncertainties as well. The effectiveness of the proposed control algorithm has been verified through simulation and experimental work using MATLAB/Simulink software and dSpace 1104 implementation board respectively.

The hydrodynamic force disturbances in direct drive valve based on voice coil motor (VCM-DDV) have greater impact on system performance. There are some weaknesses in classic Proportion integration differentiation(PID)control. In this paper, a mathematical model of the VCM-DDV is established. A double-closed loop control structure composed of position loop and current loop is presented. A novel nonlinear PID (NLPID) control strategy is applied in position loop. Fuzzy control is used to achieve self-tuning of control parameters. The design method of NLPID controller in position loop is presented in detail. Simulation and experimental results show the control strategy has a better anti-interference and robustness, superior stability and dynamic performance than classic PID and fuzzy PID in the same disturbance.

The hydrodynamic force disturbances in direct drive valve based on voice coil motor (VCM-DDV) have greater impact on system performance. There are some weaknesses in classic Proportion integration differentiation(PID)control. In this paper, a mathematical model of the VCM-DDV is established. A double-closed loop control structure composed of position loop and current loop is presented. A novel nonlinear PID (NLPID) control strategy is applied in position loop. Fuzzy control is used to achieve self-tuning of control parameters. The design method of NLPID controller in position loop is presented in detail. Simulation and experimental results show the control strategy has a better anti-interference and robustness, superior stability and dynamic performance than classic PID and fuzzy PID in the same disturbance.

It is well known that the system performance of an induction motor with indirect field oriented control degrades under the variation of rotor resistance and in the presence of external load disturbance, and the shortage of the conventional robust control approaches in considering robust stability and robust performance simultaneously is introduced briefly. In order to solve these problems, Youla parameterization based two-degree-of-freedom controller using robust design method is studied, the feedback controller is design using H_∞ mixed sensitivity to guarantee the robust stability and performance of feedback closed loop. The H₂ optimization based feedforward controller is design to obtain the robust performance of tracking even under model error. Simulation results demonstrate that the proposed approaches can improve the system performance under plant parameter variation and external disturbance.

It is well known that the system performance of an induction motor with indirect field oriented control degrades under the variation of rotor resistance and in the presence of external load disturbance, and the shortage of the conventional robust control approaches in considering robust stability and robust performance simultaneously is introduced briefly. In order to solve these problems, Youla parameterization based two-degree-of-freedom controller using robust design method is studied, the feedback controller is design using H_∞ mixed sensitivity to guarantee the robust stability and performance of feedback closed loop. The H₂ optimization based feedforward controller is design to obtain the robust performance of tracking even under model error. Simulation results demonstrate that the proposed approaches can improve the system performance under plant parameter variation and external disturbance.

This paper presents a PIR(proportional integral resonate) current control method for SPMSM(surface permanent magnet synchronous motors) in overmodulation range. The proposed method can effectively reduce THD(total harmonic distortion) of current and the torque ripple in the flux-weakening overmodulation region. In this paper, the mechanism of the disturbance rejection by the conventional method is analyzed, and a novel PIR controlled method is proposed to improve the ability of the system to reject period disturbance signals. Numerical simulations and experiments with a 7-kW prototype are carried out. The results show that the proposed method can effectively reduce harmonic current and torque ripple.

This paper presents a PIR(proportional integral resonate) current control method for SPMSM(surface permanent magnet synchronous motors) in overmodulation range. The proposed method can effectively reduce THD(total harmonic distortion) of current and the torque ripple in the flux-weakening overmodulation region. In this paper, the mechanism of the disturbance rejection by the conventional method is analyzed, and a novel PIR controlled method is proposed to improve the ability of the system to reject period disturbance signals. Numerical simulations and experiments with a 7-kW prototype are carried out. The results show that the proposed method can effectively reduce harmonic current and torque ripple.

On account of the reverse salient pole characteristic and defects of the traditional parameter identification method, this article puts forward a parameter identification method based on genetic algorithms combine with the mathematical model of the motor. This method can identify the four parameters in same time such as the stator resistance, the d-axis inductance, the q-axis inductance and the permanent magnet flux. The signal used in the method are all can be directly detected the state variables so it can reduce the influence of the other disturbance on the motor parameters identification and improve the accuracy of the parameter identification. Simulation and experimental results show that the genetic algorithm to identify the parameters has a strong robustness and convergence. Four pending identification parameters can converge to the true value in a relatively short time and has a high accuracy no matter in the different speeds, loads and control strategies. It also overcomes the drawback of high requirements in the initial parameter values which in the commen genetic algorithm to identify.

On account of the reverse salient pole characteristic and defects of the traditional parameter identification method, this article puts forward a parameter identification method based on genetic algorithms combine with the mathematical model of the motor. This method can identify the four parameters in same time such as the stator resistance, the d-axis inductance, the q-axis inductance and the permanent magnet flux. The signal used in the method are all can be directly detected the state variables so it can reduce the influence of the other disturbance on the motor parameters identification and improve the accuracy of the parameter identification. Simulation and experimental results show that the genetic algorithm to identify the parameters has a strong robustness and convergence. Four pending identification parameters can converge to the true value in a relatively short time and has a high accuracy no matter in the different speeds, loads and control strategies. It also overcomes the drawback of high requirements in the initial parameter values which in the commen genetic algorithm to identify.