Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor(PMSM)speed control systems with conventional linear active disturbance rejection control(CLADRC)strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances.In order to address these issues,this paper proposes an improved two-degree-of-freedom LADRC(TDOF-LADRC)strategy,which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning.PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately.Moreover,to evaluate the control performance of the TDOF-LADRC strategy,its stability is proven,and the influence of each controller parameter on the system control performance is analyzed.Based on it,a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances.Finally,experiments are performed on a 750 W PMSM experimental platform,and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor

In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.

Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors

Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control.

Cascaded Model Predictive Control of Six-phase Permanent Magnet Synchronous Motor with Fault Tolerant Ability

In the field of high-power electric drives, multiphase motors have the advantages of high power-density, excellent fault tolerance and control flexibility. But their decoupling control and modulation process are much more complicated compared with three-phase motors due to the increased degree of freedom. Finite control set model predictive control can reduce the difficulties of controlling six-phase motors because it does not require modulation process. In this paper, a cascaded model predictive control strategy is proposed for the optimal control of high-power six-phase permanent magnet synchronous motors. Firstly, the current prediction model of torque and harmonic subspaces are established by decoupling the six-phase spatial variables. Secondly, a cascaded cost function with fault-tolerant capability is proposed to eliminate the weighting factor in the cost function. And finally, the proposed strategy is demonstrated through theoretical analysis and experiments. It is validated that the proposed method is able to maintain excellent steady-state control accuracy and fast dynamic response while significantly reduce the control complexity of the system. Besides, it can easily achieve fault-tolerant operation under open-phase fault.

Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors

Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller.

Permanent Magnet Axial Section Shaping Optimization Surface-mounted Permanent Magnet Synchronous Motor

In this paper, a new type of harmonic injection permanent magnet shape optimization method is proposed to suppress the torque ripple of surface-mounted permanent magnet synchronous motor. The sinusoidal waveform shaping of the axial section of the permanent magnet is added with the third harmonic shaping, and the sine wave and the third harmonic are derived. The optimal ratio is 6:1. The permanent magnet no shaping, sinusoidal shaping and sinusoidal combined third harmonic shaping are compared. The results show that the sinusoidal combined third harmonic shaping design can effectively suppress the torque ripple of the surface mounted permanent magnet synchronous motor and obtain a relatively large output torque. At the same time, a method of using permanent magnet segmentation to approximately equivalently replace sine combined with third harmonic shaping design is proposed, which effectively saves the manufacturing cost of permanent magnets and provides design and research ideas for more economical and effective optimization of surface-mounted permanent magnet motors.

Research on Thermal Calculation and End Winding Heat Conduction Optimization of Low Speed High Torque Permanent Magnet Synchronous Motor

Because of its simple structure,large torque and high efficiency,permanent magnet synchronous motor of low speed and high torque is widely adopted in many fields.In this paper,a 394.5k W mining low-speed high-torque permanent magnet synchronous motor(LSHTPMSM)is regarded as the study object.According to the physical model,a three-dimensional equivalent heat transfer temperature field calculation model of the motor is built to simulate the temperature distribution of the motor under rated conditions.In terms of the serious issue of stator winding temperature increase of permanent magnet synchronous motor of low speed and high torque,the heat conduction optimization of the end of the stator winding is studied,which enhances the heat dissipation effect of the stator end winding,effectively reduces its temperature increase and temperature gradient with the winding in the slot,and improves the practical efficiency and service life of the motor.Finally,the motor temperature rise test platform is constructed for the verification of the feasibility of the optimization scheme,which provides a reference direction for the heat dissipation optimization of permanent magnet synchronous motor of low speed and high torque.

Integrated Sliding Mode Velocity Control of Linear Permanent Magnet Synchronous Motor with Thrust Ripple Compensation

In this paper,a compound sliding mode velocity control scheme with a new exponential reaching law(NERL)with thrust ripple observation strategy is proposed to obtain a high performance velocity loop of the linear permanent magnet synchronous motor(LPMSM)control system.A sliding mode velocity controller based on NERL is firstly discussed to restrain chattering of the conventional exponential reaching law(CERL).Furthermore,the unavoidable thrust ripple caused by the special structure of linear motor will bring about velocity fluctuation and reduced control performance.Thus,a thrust ripple compensation strategy on the basis of extend Kalman filter(EKF)theory is proposed.The estimated thrust ripple will be introduced into the sliding mode velocity controller to optimize the control accuracy and robustness.The effectiveness of the proposal is validated with experimental results.

Controlling chaos in permanent magnet synchronous motor based on finite-time stability theory

This paper reports that the performance of permanent magnet synchronous motor （PMSM） degrades due to chaos when its systemic parameters fall into a certain area. To control the undesirable chaos in PMSM, a nonlinear controller, which is simple and easy to be constructed, is presented to achieve finite-time chaos control based on the finite-time stability theory. Computer simulation results show that the proposed controller is very effective. The obtained results may help to maintain the industrial servo driven system＇s security operation.

Full-order sliding mode control of uncertain chaos in a permanent magnet synchronous motor based on a fuzzy extended state observer

A full-order sliding mode control based on a fuzzy extended state observer is proposed to control the uncertain chaos in the permanent magnet synchronous motor. Through a simple coordinate transformation, the chaotic PMSM model is transformed into the Brunovsky canonical form, which is more suitable for the controller design. Based on the fuzzy control theory, a fuzzy extended state observer is developed to estimate the unknown states and uncertainties, and the restriction that all the system states should be completely measurable is avoided. Thereafter, a full-order sliding mode controller is designed to ensure the convergence of all system states without any chattering problem. Comparative simulations show the effectiveness and superior performance of the proposed control method.

Fractional-order permanent magnet synchronous motor and its adaptive chaotic control

In this paper we investigate the chaotic behaviors of the fractional-order permanent magnet synchronous motor（PMSM）.The necessary condition for the existence of chaos in the fractional-order PMSM is deduced.And an adaptivefeedback controller is developed based on the stability theory for fractional systems.The presented control scheme,which contains only one single state variable,is simple and flexible,and it is suitable both for design and for implementation in practice.Simulation is carried out to verify that the obtained scheme is efficient and robust against external interference for controlling the fractional-order PMSM system.

Impulsive control of permanent magnet synchronous motors with parameters uncertainties

The permanent magnet synchronous motors （PMSMs） may have chaotic behaviours for the uncertain values of parameters or under certain working conditions, which threatens the secure and stable operation of motor-driven. It is important to study methods of controlling or suppressing chaos in PMSMs. In this paper, robust stabilities of PMSM with parameter uncertainties are investigated. After the uncertain matrices which represent the variable system parameters are formulated through matrix analysis, a novel asymptotical stability criterion is established. Some illustrated examples are also given to show the effectiveness of the obtained results.

Application of neural networks for permanent magnet synchronous motor direct torque control

Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.

Comparison of Two Novel MRAS Based Strategies for Identifying Parameters in Permanent Magnet Synchronous Motors

Two model reference adaptive system （MRAS） estimators are developed for identifying the parameters of permanent magnet synchronous motors （PMSM） based on the Lyapunov stability theorem and the Popov stability criterion, respectively. The proposed estimators only need online measurement of currents, voltages, and rotor speed to effectively estimate stator resistance, inductance, and rotor flux-linkage simultaneously. The performance of the estimators is compared and verified through simulations and experiments, which show that the two estimators are simple, have good robustness against parameter variation, and are accurate in parameter tracking. However, the estimator based on the Popov stability criterion, which can overcome parameter variation in a practical system, is superior in terms of response speed and convergence speed since there are both proportional and integral units in the estimator, in contrast to only one integral unit in the estimator based on the Lyapunov stability theorem. In addition, the estimator based on the Popov stability criterion does not need the expertise that is required in designing a Lyapunov function.

Finite-Control-Set Model Predictive Control of Permanent Magnet Synchronous Motor Drive Systems——An Overview

Permanent magnet synchronous motors(PMSMs)have been widely employed in the industry. Finite-control-set model predictive control(FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.

Adaptive synchronization of chaos in permanent magnet synchronous motors based on passivity theory

An adaptive synchronization control method is proposed for chaotic permanent magnet synchronous motors based on the property of a passive system. We prove that the controller makes the synchronization error system between the driving and the response systems not only passive but also asymptotically stable. The simulation results show that the proposed method is effective and robust against uncertainties in the systemic parameters.

Analysis and Design of Surface Permanent Magnet Synchronous Motor and Generator

This paper presents an analytical method to design the high-efficiency surface permanent magnet synchronous motor(SPMSM)or generator(SPMSG).The air-gap and permanent magnet size can be approximately determined based on our mathematics model,which is the most important part of SPMSM design.From our method,we can know that motor’s power out torque is related to the torque angle that we selected in our design and it affects the air-gap and permanent magnet size.If we choose a low torque angle,the motor or generator’s overload power handing capability will increase.The embrace value has a vital place in designing a motor or generator due to its effects on air gap flux density,cogging torque,efficiency and so on.In order to avoid the knee effect,the working point of the permanent magnet we selected in the design should be bigger than 0.5.The developed 36 slots,4 poles,surface mound permanent generator is proposed.The corresponding finite element analysis(FEA)model is built based on our design method.Structure optimization includes stator and rotor structure size,permanent magnet size,magnetic bridge and air gap length which are analyzed and simulated by ANSYS Maxwell 2D FEA.Thermal analysis is conducted,and the housing of the alternator is designed.The alternator prototype is fabricated and tested based on our design.

Position Sensorless Control for Permanent Magnet Synchronous Motor Using Sliding Mode Observer

An approach of position sensorless control for permanent magnet synchronous motor （ PMSM ） is put forward based on a sliding mode observer. The mathematical model of PMSM in a stationary αβ reference frame is adopted, and the system is controlled by the digital signal processor （ DSP; TMS320LF2407 according to the control achieve closed loop operation of the motor, the stator theory of sliding mode observer. In order to magnetic field should be vertical with the rotor magnetic field and be synchronous with rotor rotating, so the position and speed of PMSM is estimated in real time and the estimated position is modified continuously. The simulation results indicate that the proposed observer has high precision is more robust to the parametric variation and load in estimation of PMSM position and speed, and torque disturbance.

Optimization of Vibration and Noise Performance of Permanent Magnet Synchronous Motor for Electric Vehicles

In the design of the motor used for electric vehicles(EVS),vibration and noise problems are often ignored,which reduce the reliability and service life of the motor.In this paper,an interior permanent magnet synchronous motor(IPMSM)with high power density is taken as an example,and its electromagnetic vibration and noise problem is investigated and optimized.Firstly,the factors that generate the electromagnetic force harmonic of IPMSM are analyzed by theoretical derivation.Furthermore,the mode and electromagnetic harmonic distribution of the motor are calculated and analyzed by establishing the electromagnetic-structure-sound coupling simulation model.Then,by combining finite element method(FEM)with modern optimization algorithm,an electromagnetic vibration and noise performance optimization method is proposed in the electromagnetic design stage of the motor.Finally,an IPMSM is optimized by this method for electromagnetic vibration and noise performance.The results of comparison between before and after optimization prove the feasibility of the method.

Vector control of permanent magnet synchronous motor based on dynamic matrix control

Aiming at the control problem of strongly nonlinear and coupled permanent magnet synchronous motor(PMSM)oil rig,this paper presents a predictive control method based on dynamic matrix model.In this method,the dynamic matrix algorithm using multistep prediction technique is applied to the speed loop control of the motor vector control.And its control effect is compared with the traditional proportional integral(PI)control of the motor.By comparing the initial dynamic response and the steady-state recovery under load interference of the two methods,it is shown that the dynamic response and the robustness of the motor controlled by the new method is better than that controlled by conventional PI method.And the feasibility of new control in the application of PMSM oil rig is verified.