Model Of Permanent Magnet Linear Synchronous Motor Research Articles

Adaptive super-twisting-based nonsingular fast terminal sliding mode control of permanent magnet linear synchronous motor

In this study, to reduce the impact that permanent magnet linear synchronous motor (PMLSM) servo system on the sensitivity of external and internal interferences, an adaptive super-twisting-based nonsingular fast terminal sliding mode control (AST-NFTSMC) scheme is put forward. First of all, the mathematical model of PMLSM contains uncertainties is set up, and the control law is established to make position signal converge to given state asymptotically. Second, by introducing the super-twisting algorithm, the chattering caused by nonlinear switching function in traditional method is weakened. However, in actual industrial situations, it is difficult to determine the boundary of lumped disturbance, which makes the switching gains in super-twisting algorithm cannot be accurately selected. Therefore, an adaptive law is introduced to adjust the switching gains online, so that the gains can be dynamically adjusted within a limited range during operation, so as to further weaken chattering. Finally, the practicability of AST-NFTSMC is proved in theory and verified by system experiments. The experimental results prove that AST-NFTSMC can significantly weaken chattering, and result in robust control performance.

A Novel Robust Adaptive Nonsingular Fast Integral Terminal Sliding Mode Controller for Permanent Magnet Linear Synchronous Motors

To realize the high-precision tracking control of permanent magnet linear synchronous motor (PMLSM) in complex working conditions, a control system with strong robustness must be equipped for PMLSM, so this article proposes a novel robust adaptive nonsingular fast integral terminal sliding mode control (ANFITSMC) strategy. First, a dynamical mathematical model of PMLSM is established to describe the thrust and unknown uncertainty in the motion process. Second, considering that the uncertain factors, such as external disturbances and high-frequency noises in the system, may cause the degradation of position tracking accuracy, a nonsingular fast integral terminal sliding mode control (NFITSMC) method that only requires position and velocity information to estimate the lumped uncertainty of the system is designed. Meanwhile, the adaptive control algorithm is used to estimate the lumped uncertainty dynamically in real time, thus weakening the chattering and improving the tracking accuracy. Also, the stability of this control system is proven by utilizing the Lyapunov stability theory. Finally, the high-precision positioning experimental platform is used to carry out experimental tests with different position trajectory commands. The experimental results show that the proposed ANFITSMC method not only enables the system to have higher control accuracy but also ensures a more robust performance.

Integrated Predictive Control of PMLSM Current and Velocity Based on ST-SMO

To enhance the control performance of a permanent magnet linear synchronous motor (PMLSM) and to improve its dynamic response performance and steady-state accuracy, a PMLSM model predictive integrated control (MPC) system based on a super-twisting sliding mode observer (ST-SMO) is proposed. According to the mathematical model of a PMLSM, this paper designs a three-step model to predict the comprehensive control correction factor, optimize the prediction speed and current, reduce the response time, and enhance the system’s stability. Meanwhile, in order to solve the problem of the PMLSM’s high dependence on mechanical sensors, the ST-SMO is introduced to observe the rotation speed of PMLSM, which has better tracking performance and observation accuracy than a traditional sliding mode observer (SMO). Finally, the experimental verification is carried out on the PMLSM experimental platform. The software simulation and hardware experiment results show that the control system designed in this paper not only simplifies the overall structure of the system, but it also has better control performance and tracking ability. Compared with traditional control methods and SMO, it has better control performance, stability, and speed-tracking performance.

Sensorless Control of Permanent Magnet Linear Synchronous Motor Based On Double Sliding Mode

Background & Objective: This document presents a dual sliding mode vector control method to estimate speed and position of Permanent Magnet Linear Synchronous Motor (PMLSM). Methods: Firstly, the motor simulation model is built based on the mathematical model of PMLSM. For the sake of solving the problems of the jitter and position angle deviation in the traditional SMO, the inverse hyperbolic tangent function is used and the software phase-locked loop algorithm is introduced, and the gain of exponential approach rate is improved to change the real-time, so as to eliminate the problems of high-frequency jitter and angle deviation. Secondly, global fractional order integral sliding mode control (GFOISMC) is used to replace PI control to eliminate jitter and improve the robustness to load disturbance. Finally, the dynamic performance of the system under constant speed no-load and constant speed sudden load is simulated. Results: The simulation result proves a proposed dual sliding mode control strategy combining the improved SMO and GFOISMC that can effectively reduce the jitter and improve robustness. Conclusion: In this paper, two sensorless control strategies are compared and their robust performance is studied. The two control scheme is simulated in the MATLAB/Simulink environment.

A Novel Robust Super-Twisting Nonsingular Terminal Sliding Mode Controller for Permanent Magnet Linear Synchronous Motors

For accurate position tracking and robust control of permanent magnet linear synchronous motor (PMLSM) servo systems against various uncertainties, such as parameter change, load disturbance, friction force, and so on, this article proposes a novel super-twisting nonsingular terminal sliding mode control method based on a high-order sliding mode observer. First, a dynamic model of PMLSM with uncertainties is established. A novel nonsingular terminal sliding mode function combined with the super-twisting algorithm is then proposed to design a robust super-twisting nonsingular terminal sliding mode controller, which ensures the system convergence to the equilibrium state within a finite time, effectively eliminating the chattering phenomenon and improving the system robustness. To further improve the system tracking performance and anti-interference ability, a high-order sliding mode observer is used to estimate the system uncertainties. The effective tracking performance and robustness of the proposed control method are validated by the experimental results.

Continuous Fast Terminal Sliding Mode Control of Permanent Magnet Linear Synchronous Motor

The permanent magnet linear synchronous motor(PMLSM) with direct driving method, which can obtain faster speed and acceleration, has been widely used in the industrial field in recent years. However, due to the lack of transmission links and the influence of nonlinear factors, the control of PMLSM is more difficult. In order to solve the problem that the control system is easy to be affected by nonlinear friction, external disturbance and other uncertain factors, the mathematical model of PMLSM with uncertain factors is established, and a continuous fast terminal sliding mode control(TSMC) method is proposed in this paper. The exponential reaching law(ERL) is used in this method to make the motion track reach the sliding surface quickly and effectively weaken the chattering of the system. The singular problem in the fast TSMC is solved by selecting the parameters to ensure the robustness of the system and improve the response speed of the system. The simulation results show that the continuous fast TSMC method has the ability of accurate position tracking and fast response of the system, so it has great practical value.

Co-simulation of self-adjusting fuzzy PI controller for the robot with two-axes system

This paper presents the co-simulation of the self-adjusting fuzzy PI controller to control a two-axes system. Each axis was driven by a permanent magnet linear synchronous motor (PMLSM). The position and speed controller used the fuzzy PI algorithm with parameters adjusted by a radial basis function neural network (RBFNN). The vector control was applied to the decoupled effect of the PMLSM. The field programmable gate array (FPGA) was used to control both axes of the system. The very high-speed integrated circuit-hardware description language (VHDL) was developed in the Quartus II software environment, provided by Altera, to analyze and synthesize designs. Firstly, the mathematical model of PMLSM and fuzzy PI was introduced. Secondly, the RBFNN adjusted the knowledge base of the fuzzy PI. Thirdly, the motion trajectory was introduced for testing the control algorithm. Fourthly, the implementation of the controller based on FPGA with the FSM method and the structure of co-simulation between Matlab/Simulink and ModelSim were set up. Finally, discussion about the results proved the effectiveness of the control system, determining the exact position and trajectory of the XY axis system. This research was successful in implementing a two-motor controller within one chip.

Intelligent second‐order sliding mode control for permanent magnet linear synchronous motor servo systems with robust compensator

In this study, an intelligent second-order sliding mode control (SMC) method combining second-order SMC (SOSMC) and recurrent radial basis function neural network (RRBFNN) applicable to the permanent magnet linear synchronous motor (PMLSM) is proposed to achieve high-performance servo control fields. On the basis of a dynamic model of PMLSM and the SMC theory, the chattering problem in SMC is weakened and the tracking accuracy is improved by the design of SOSMC. As for the boundary of the uncertainty factors is difficult to obtain, the optimal performance of SOSMC is hard to achieve, the RRBFNN uncertainty observer is introduced for estimating the value of the uncertainty factors. Owing to the strong learning ability, the network parameters can be trained online. Besides, a robust compensator is developed to suppress the uncertainties such as approximation error, optimal parameter vector and higher Taylor series for further improving the robustness. Moreover, the adaptive learning algorithms are obtained by using the Lyapunov theorem to guarantee the asymptotical stability of the system. The experiments demonstrate that the proposed scheme provides high performance dynamic characteristics and strong robustness to uncertainties.

Constant switching frequency model predictive control for permanent magnet linear synchronous motor

Aim: This paper proposes constant switching frequency model predictive control (CSF-MPC) for a permanent magnet linear synchronous motor (PMLSM) to improve the steady state and dynamic performance of the drive system.
 Methods: The conventional finite control set model predictive control (FCS-MPC) can be combined with a pulse width modulation (PWM) modulator due to an effective cost function optimization algorithm which is from the idea of dichotomy. In the algorithm, all the voltage vectors in the constrained vector plane are dynamically selected and calculated through iteration. The whole system including control algorithm and mathematical model of PMLSM is built and tested by simulation using MATLAB/Simulink. Besides, the control algorithm is tested in the FPGA controller through FPGA-in-the-Loop test.
 Results: With the modern digital processors or control hardware such as digital signal processors (DSPs) or field programmable gate arrays (FPGAs), the algorithm can be easily executed in less than 10-micro second. This is very proper for industrial applications. The proposed control algorithm is implemented on FPGA and tested by FPGA-in-the-Loop method. The proposed control algorithm can improve the performance of drive system greatly.
 Conclusion: The proposed CSF-MPC for PMLSM not only keeps the same dynamic transient performance as FCS-MPC but also greatly decreases the torque ripple in steady state. Furthermore, CSF-MPC is also robust to parameter variations. Simulation and FPGA-in-the-Loop results illustrate that CSF-MPC has an attractive performance for PMLSM drives.

PMLSM position control based on continuous projection adaptive sliding mode controller

ABSTRACTIn this paper, the design of projection-based Adaptive Sliding Mode Controller (ASMC) is presented for position control of Permanent Magnet Linear Synchronous Motor (PMLSM) with unknown mover mass. The PMLSM model was first established and a vector control based on field orientation is used to decouple the cross-coupling in motor model. ASMC has been adopted to deal with the unknown mover mass and to give robust operation against external load thrust. Based on the Lyapunov method, the stability of adaptive sliding mode-controlled PMLSM has been proven and the adaptive law has been developed. Additionally, a continuous projection operator is applied to adaptive law such as to enforce the estimated mover mass within a pre-specified bound. The performance of ASMC based on continuous projection operator is investigated via simulation results within MATLAB environment. Also, a comparison study in ASMC performance is made due to the inclusion continuous and discontinuous projection operators. The simulated results showed that ASMC based on continuous projection gives better performance than that based on discontinuous one.

A High-Bandwidth and Strong Robust Current Control Strategy for PMLSM Drives

As an ideal current control method, the superiority of the predictive current control (PCC) is seriously weakened by the one-step control delay and parameter mismatch issues. To acquire the high dynamic and static characteristics, this paper studies an improved PCC scheme for the permanent magnet linear synchronous motor (PMLSM) drives. First, the discrete-time model of PMLSM considering the parameter variation is established. Second, the formation mechanisms of these two issues are analyzed in detail, respectively. Meanwhile, through replanning the timing sequence logic, the one-step control delay issue is solved. Furthermore, based on the super-twisting algorithm, the super-twisting sliding-mode observer (STSMO) is constructed to compensate for the parameter disturbance. To further improve the dynamic property and lower the chattering, a third-order STSMO is presented in comparison with the second-order STSMO. In the meantime, the estimated currents can be utilized in the solution of one-step delay issue. At last, on the PMLSM testing platform based on the aerostatic guide, the corresponding experimental results are shown to verify the effectiveness and correctness of the proposed method.

A Robust Adaptive Sliding Mode Control for PMLSM with Variable Velocity Profile Over Wide Range

An adaptive robust variable structure speed controller is designed for wide range of desired velocity control of a Permanent Magnet Linear Synchronous Motor (PMLSM). This is performed for comprehensive nonlinear model of PMLSM including non-idealities such as detent force, parameter uncertainty, unpredicted disturbance and nonlinear friction. The proposed method is based on the robust Sliding Mode Control (SMC) in combination with an adaptive strategy for a wide range of velocity. The simulation results are provided for the above mentioned comprehensive model of PMLSM with a variable velocity profile. Moreover, as an evaluation criterion, a Proportional-Integral (PI) controller is designed whose parameters are optimally tuned by the Particle Swarm Optimization (PSO) algorithm for better comparison.

APPLICATION OF ADAPTIVE VARIABLE SPEED BACK-STEPPING SLIDING MODE CONTROLLER FOR PMLSM POSITION CONTROL

In this research, an adaptive variable speed back-stepping sliding mode controller (AVSBSMC) is proposed to control the permanent magnet linear synchronous motor (PMLSM) on high-precision positioning servo system platform. This controller combines the dynamic features of variable speed control (VSC) and the positioning characteristics of adaptive back-stepping sliding mode control (ABSMC). Firstly, the detailed dynamic machine model of PMLSM is established. Secondly, the proportional-integral-derivative (PID) and ABSMC controllers are proposed to compensate the uncertainties in position control. Then, the one provides the better servo performances is the position controller in the motor system. Thirdly, the variable speed controller (VSC) and each segment of the variable speed sliding functions are designed to combine with the ABSMC controller. Switching control is then used to change the system control mode accomplishing the high-precision positioning control. Our experimental results demonstrate that the AVSBSMC enhance the positioning accuracy of linear motor and reduce the transient overshoot effectively.

Research of Speed Regulating System Based on New Fuzzy PI Control

In order to further improve on the static and dynamic performance of the permanent magnet linear synchronous motor (PMLSM) speed regulating system, the traditional PI control is combined with the fuzzy control to achieve PI parameters self-regulating. In this paper, on the basis of studying the mathematic model of PMLSM, the resisting integral saturation method are adopted to eliminate the integral saturation which the traditional PI causes. the fuzzy control is introduced into the PI control to realize to the self-optimization of the PI parameters. The simulation results show the resisting integral saturation PI control system based on the fuzzy control algorithm has better static and dynamic performances and stability, and possesses stronger anti-strike performance. Therefore, the new control system resolves the problems which the traditional PI controller cant achieve the most optimization because of the difficulty of the parameter regulating.

Detent Force Analysis of Permanent Magnet Linear Synchronous Motor for Bearing Grinding Machine Application

The detent force of permanent magnet linear synchronous motor (PMLSM) leads to the thrust ripple, vibration and noise inbearing grinding machines, In order to overcome the negative effect, detent force needs to be decreased. Through theanalytical andfinite element methods, two main components of detent force are investigated in this paper. Firstly, finite element analysis (FEA) and fast Fourier transform (FFT) are employed to analyze the end force. Then athree dimensional (3-D) FEA model of a short secondary PMLSM with skewed poles is erected and the cogging force is studied.Compared with the two dimensional (2-D) model of PMLSM without skewed poles, the detent force is remarkably reduced.

Thrust Ripple of a Permanent Magnet LSM With Step Skewed Magnets

This paper analyzes the thrust characteristics of the investigated permanent magnet linear synchronous motor (PMLSM) and discusses their differences with those of rotary motors. It shows that the main components of the thrust ripple are second, fourth, and sixth harmonics, which is produced by end-effect, not the 12th harmonic caused by cogging. The ripple suppression abilities of magnet step-skew method are analyzed through skew factors of thrust harmonics and effective electromagnetic thrust. The optimal step number and skew angle for PMLSM are studied with comparison to those of rotary motor. A 2-D FEM algorithm for the asymmetric PMLSM model analysis is investigated, with which the aforesaid skew step number selection and optimal skew angle are validated.

Detection and Analysis of Stator Winding Inter-Turn Short Circuit Fault in Permanent Magnet Linear Synchronous Motor

A two-dimensional finite element model of PMLSM is build based on the finite element analysis software Magnet to research the diagnosis of stator winding inter-turn short circuit fault in PMLSM. The velocity, thrust, the stator current performance curve are obtained by simulation using Magnet when PMLSM is normal and under different extent inter-turn short circuit fault, the harmonic content of speed and thrust are analyzed using Matlab / Simulink , the conclusion that the thrust of the harmonic content is used as the Permanent Magnet Linear Synchronous Motor (PMLSM) stator inter-turn short circuit fault feature is proposed , which provided a basis for detection of stator winding inter-turn short circuit fault in PMLSM.

Finite element analysis of load characterisitic and parameters in permanent magnet linear synchronous motor with structure slots per phase per pole less than 1

By stability achievement of permanent magnet linear synchronous motor(PMLSM) with slots per phase per pole less than 1(q1) fractional slot, thrust force density becomes the key point in analysis and design of the motor. To analyze the load characteristics, a finite element method(FEM) model of PMLSM is set up based on 2D electromagnetic field equations. Taking influence of end-leakage to PMLSM into account, open-boundary condition is used to improve the precision of analysis. With fixed three-phase winding current of fractional slot from space-time vectogram, relaxation factor method is used to adjust angle α. By iterating the normal rated thrust, load characteristic and parameters are obtained by instantaneous current method. Experimental prototype is used for parameter measurement. Comparing the FEM calculation with actual measurements, results show that FEM based model can confirm the load characteristic and obtain the parameters and power-angle characteristic of PMLSM. Direct-quadrature axis inductances give a good reference to the motion control of PMLSM.

Applications of unscented Kalman filter on position sensorless control of permanent magnet linear syncheonous motor

For a variety of nonlinear estimation problems, the unscented Kalman filter (UKF) is a superior alternative to the extended Kalman filter (EKF). The effectiveness of UKF for position sensorless control of permanent magnet linear syn- chronous motor (PMLSM) is investigated. At first, the PMLSM model used in the estimation algorithm is established, then, the position sensorless PMLSM drive system based on UKF is presented. Via simulations and experiments, the effectiveness of UKF for position sensorless control of PMLSM is verified. And, a comparison of estimation performance of UKF and EKF for estimating position and speed is carried out. The simulation and experiment results indicate that UKF performs equivalently with EKF, but the computational time of UKF is more than that of EKF. For estimating position and speed of PMLSM, the EKF is a better choice than UKF.