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.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

Model-free Speed Control of Single-phase Flux Switching Motor with an Asymmetrical Rotor

This paper proposes and implements a model-free open-loop iterative learning control(ILC)strategy to realize the speed control of the single-phase flux switching motor(FSM)with an asymmetrical rotor.Base on the proposed winding control method,the asymmetrical rotor enables the motor to generate continuous positive torque for positive rotation,and relatively small resistance torque for negative rotation.An initial iteration coefficient and variable iteration coefficient optimized scheme was proposed based on the characteristics of the hardware circuit,thereby forming the model-free strategy.A series of prototype experiments was carried out.Experimental results verify the effectiveness and practicability of the proposed ILC strategy.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Enhanced Fuzzy Logic Control Model and Sliding Mode Based on Field Oriented Control of Induction Motor

In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.

Analyzing the Combination Effects of Repetitive Transcranial Magnetic Stimulation and Motor Control Training on Balance Function and Gait in Patients with Stroke-Induced Hemiplegia

Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.

DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

The Brushless DC Motor drive systems are used widely with renewable energy resources.The power converter controlling technique increases the performance by novel techniques and algorithms.Conventional approaches are mostly focused on buck converter,Fuzzy logic control with various switching activity.In this proposed research work,the QPSO(Quantum Particle Swarm Optimization algorithm)is used on the switching state of converter from the generation unit of solar module.Through the duty cycle pulse from optimization function,the MOSFET(Metal-Oxide-Semiconductor Field-Effect Transistor)of the Boost converter gets switched when BLDC(Brushless Direct Current Motor)motor drive system requires power.Voltage Source three phase inverter and Boost converter is controlled by proportional-integral(PI)controller.Based on the BLDC drive,the load utilized from the solar generating module.Experimental results analyzed every module of the proposed grid system,which are solar generation utilizes the irradiance and temperature depends on this the Photovoltaics(PV)power is generated and the QPSO with Duty cycle switching state is determined.The Boost converter module is boost stage based on generation and load is obtained.Single Ended Primary Inductor Converter(SEPIC)and Zeta converter model is compared with the proposed logic;the proposed boost converter achieves the results.Three phase inverter control,PI,and BLDC motor drive results.Thus the proposed grid model is constructed to obtain the better performance results than most recent literatures.Overall design model is done by using MATLAB/Simulink 2020a.

基于DCS-惯性权重组合的柔性机械臂运动轨迹控制系统研究

为了有效调控机械臂运动幅度,避免柔性机械臂实际运动轨迹与目标轨迹发生较大的偏差,设计一种基于分散控制系统(DCS)-惯性权重组合的柔性机械臂运动轨迹控制系统,它是一个集合了计算机、通信、显示和控制的计算机系统,该系统由过程控制和过程监控。通过DCS算法控制监测对象行为幅度并计算柔性机械臂惯性权重,利用DCS-惯性权重组合求解素数控制指标的具体数值,实现了对柔性机械臂运动轨迹控制系统的软件设计。实验结果表明,DCS-惯性权重组合算法作用下的机械臂末端坐标在横轴、纵轴、空间轴方向上的运动幅值均可以被控制在10个单位长度之内,并且在0.52 s内进入机械臂运动轨迹最佳控制状态,运动轨迹差值最大仅为0.01 rad,验证了该系统具备可行性和有效性。

EFFECTIVE DOUBLE LOOP CONTROL FOR A SQUARE WAVE BRUSHLESS DC MOTOR

A new type of brushless DC motor has been developed by using a square wave rare earth permanent magnet synchronous motor with its double loop control circuit. The double loop control scheme of the drive system yields a combination of desired characteristics including simplified control structure, small ripple torque, high speed accuracy, wide operating speed range, and fast dynamic response. Experimental results confirm excellent characteristics of the motor.

基于模糊BP神经网络的智能轮椅BLDCM控制

现阶段多数轮椅电机仍使用传统PID控制,该控制方式存在控制精准度较低、超调量较大以及抗扰动能力差等问题。为解决以上问题,通过对无刷直流电机进行研究,在分析了其控制方法后,提出一种基于模糊BP神经网络的BLDCM控制方法。首先,研究了BLDCM结构并搭建数学模型。其次,在模型基础上构建了模糊BP神经网络PID控制器。最后,在Matlab/Simulink中搭建整个电机控制系统进行三种不同工况下的运动控制仿真,并与传统PID控制算法进行对比。实验结果表明:模糊BP神经网络PID控制策略能获得更好的PID控制参数,具有良好的抗扰动能力,有效的改善了整个轮椅控制系统的动态性能。

基于回流功率优化的直流微网DC-DC变流器超螺旋滑模控制

针对直流微网系统中双有源桥直流变换器在系统发生扰动时动态特性差及在单移相调制下变换器效率不高等问题,该文在扩展移相调制下提出一种结合回流功率优化的超螺旋滑模控制策略。首先,分析双有源全桥(dual-active-bridge,DAB)变换器在扩展移相调制下两种模式的传输功率、回流功率数学模型及软开关特性,并以传输功率数学模型为基础建立DAB变换器的降阶模型。其次,以回流功率作为目标函数,以传输功率和软开关特性作为约束条件,通过Karush-Kuhn-Tucker(KKT)条件法寻找最优移相比组合;利用DAB变换器降阶模型设计超螺旋滑模控制中的等效部分,采用超螺旋算法作为切换部分,这两部分与内移相比D1共同作用生成外移相比D2,用于调节变换器的输出电压。最后进行了仿真及实验验证,实验结果表明:在负载投切、输入电压突变、参考电压改变时变换器具有良好的动态性能,同时能有效地减小回流功率。

基于时变权重模型预测的双向DC-DC优化控制方法

双向DC-DC变换器是电动汽车的关键电压变换部件,提高其动态负载下的响应速度与鲁棒性对电动汽车低压供电系统有重要意义。提出一种基于模糊时变权重的MPC(model predictive control)控制方法。基于状态空间平均法建立变换器动态模型。基于MPC原理搭建变换器MPC模型,实现对电压的跟踪控制;在分析权重对动态负载下电压跟踪性能的影响的基础上,设计权重模糊调节器,实现权重的在线调节。基于HM-cSPACE搭建实验平台验证所提方法的准确性。在Matlab/Simulink环境下与PI控制和传统MPC控制进行对比,结果表明:在负载变化时采用时变权重MPC控制的变换器有更好的动态性能和鲁棒性,超调量降低26.1%。该方法对提高双向DC-DC变换器动态负载下的优化控制具有重要意义。

固态变压器中隔离双向DC/DC变换器扩展移相下虚拟电流控制策略

该文以固态变压器后级隔离双向DC/DC变换器为重点研究对象,提出一种扩展移相下虚拟电流控制策略。通过分析后级变换器在扩展移相传输功率下相移量关系以获得最小电流应力最优解来提高变换器的传输效率,减少器件损耗。同时通过虚拟电流控制思想在线估算传输功率来提高系统动态响应性能,减少电流传感器使用。最后,对该文所提出的扩展移相下虚拟电流控制与扩展移相控制进行实验对比分析,验证了扩展移相下虚拟电流控制策略具有降低电流应力,显著提高变换器的动态响应的优点。

三有源桥DC-DC变换器广义状态空间平均模型及控制策略研究

基于移相加占空比控制策略的三有源桥TAB(triple active bridge)DC-DC变换器具有效率高和软开关范围可扩展等优点,但其小信号建模过程复杂、闭环控制环路参数整定困难。针对该问题,提出1种TAB工作在移相加占空比控制下的全阶连续广义状态平均建模和PI控制器设计方法。首先,分析TAB的运行原理和Y型等效结构;然后,结合移相加占空比控制的特点和交流方波源等效方法,推导出TAB的广义状态空间平均模型;接着,在推得模型的基础上求得输入到输出的传递函数,设计出PI控制器参数。最后,结合数字仿真及样机实验验证了所提方法的正确性及有效性。

基于MPC的耦合电感飞跨电容双向DC/DC变换器功率均衡解耦控制策略

耦合电感功率变换器因耦合电感阻抗、电感值等参数差异易导致功率不均衡。针对耦合电感飞跨电容双向DC/DC变换器,提出一种基于模型预测控制(MPC)的功率均衡解耦控制策略。通过对变换器原理进行分析,建立基于电感电流解耦的数学模型,得到包括电感电流和飞跨电容电压等6个控制变量的解耦控制方法。在此基础上,提出基于MPC的功率均衡解耦控制策略。同时,为降低MPC算法的运算负荷,根据解耦控制模型重构模型预测价值函数,实现各控制变量独立动态寻优,使系统能在稳定控制输出电压及飞跨电容电压的同时,实现两相耦合电感的功率均衡控制。最后,通过理论分析及实验对所提策略进行有效验证。

基于LDC1101的电涡流传感器设计

传统的模拟式电涡流传感器存在容易受到干扰、电路设计复杂的问题而利用现场可编程门阵列(FPGA)或复杂可编程逻辑器件(CPLD)软件实现测量电路和输出信号的数字式电涡流传感器调试复杂的问题。针对以上问题,设计了基于LDC1101的数字化电涡流传感器,实现载波信号发生和测量信号解调于一体,并把测量结果通过SPI通信传输给控制器。每个传感器模块由1个LDC1101芯片、1个电涡流传感线圈和1个匹配电容组成。极大简化了电路设计以及调试难度。此传感器测量方法已用于无轴承永磁电机的悬浮控制中对转子磁钢的径向位置测量中。通过4只传感器安装在信号采集电路板上,差分测量然后计算出转子的x和y位置。试验结果表明,该方法分辨率高,可靠性好。

三电平混合全桥DC-DC变换器回流功率优化控制

针对三电平混合全桥双向DC-DC变换器存在的回流功率较大的问题,本文以回流功率最小化为目标,提出了一种基于双重移相控制的回流功率优化控制策略。首先,建立了三电平混合全桥DC-DC变换器的数学模型,分析了变换器回流功率和传输功率的特性关系;然后,以回流功率作为目标函数,通过KKT条件法将不同模式的等式和不等式约束条件转换为约束函数,并构建拉格朗日多项式函数求最佳移相比组合;最后,为提高系统动态响应的快速性,采用了环内直接功率控制方法,实现了变换器在面对突发情况时系统能迅速实现动态响应。仿真结果表明,在输入电压和负载突变时,本文提出的改进优化控制策略可以有效减小回流功率,提高系统的动态响应性能。

高频链AC-DC矩阵变换器的变控制频率软开关调制策略

针对高频链AC-DC矩阵变换器的高效率要求,提出了一种变控制频率软开关调制策略。该调制策略在基于零矢量嵌入的分段同步控制策略基础上,以单控制周期平均功率不变为原则,通过改变控制周期长度,并调整一个控制周期内的电压矢量排布,优化脉冲宽度,使变换器在换流时全部开关器件的零电压开通成为可能。通过仿真分析和实验证明,采用本文提出的变控制频率调制策略,变换器在整流和逆变模式下,均可实现网侧电流三相平衡正弦,功率因数达到0.981,输出电压纹波小,最高效率达到96.9%,实现了高性能、高效率运行。

基于PWM+移相的双有源半桥DC-DC变换器分析及其控制

该文针对双有源半桥(DAHB)DC-DC变换器宽电压范围运行下电容电压计算不准确、单移相控制粗放等不足,提出一种基于PWM+移相的三自由度优化控制(TFC)策略。首先,基于DAHB的数学模型,推导桥臂串联电容稳态电压表达式。在此基础上,从最小化回流功率角度得到三自由度控制的最优开关模式,推导了电流、功率等关键电气量的解析表达式,并获得以电流应力最小化为目标的包含等式和不等式约束的局部最优解方程组。其次,针对最优方程组难以解析求解的问题,采用模型简化+线性近似的方法求取其局部最优解,得到DAHB全工况PWM+移相的三自由度优化控制策略。然后,分析所提出的三自由度优化控制下DAHB变换器的软开关特性。最后,通过仿真及实验验证了桥臂串联电容稳态电压表达式的正确性和三自由度优化控制策略的有效性。