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。

Anti-reverse rotation startup method for sensorless brushless DC motor

In order to start up the brushless DC motor （BLDCM） without reverse rotation and smoothly switch the running state of the motor, a novel startup and smoothly switching method for a sensodess BLDCM is presented. Based on the saturation effect of the stator iron, six short voltage pulses are applied to determine the initial rotor position and the rotor can be found within 60°. After that, a series of short and long voltage pulses are used to accelerate the motor and the variation of the response current is utilized to detect the rotor position dynamically. When the motor reaches a certain speed at which the back-electromotive force （EMF） method can be applied, all the power devices are turned off and the running state of the motor is smoothly switched at the moment determined by the relationship between the terminal voltage waveform and the commutation phases. The experimental results verify the feasibility and validity of the proposed method.

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。

Improved single-neuron PID controller for DC motor applied in robot system

An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.

永磁同步电机双向DC/DC变换器混合储能设计

为了提高永磁同步电机的发电效率,设计一种永磁同步电机双向DC/DC变换器混合储能方案,并开展性能仿真分析。利用双向DC/DC变换器连接储能部件与负载母线,该变换器的控制性能对系统整体动/静态性能存在明显影响。研究结果表明:在Buck模式下仿真测试得到,双向DC/DC变换器高压侧电流逐渐升高,产生了持续上升的最高输出功率。双向DC/DC变换器与Buck电路达到了合理的参数,能够达到混合储能系统要求达到的稳定性与快速性控制标准。本设计的双向DC/DC变换器主电路与Boost电路各项参数处于较优的状态,能够实现对混合储能系统进行稳定高效控制的目标。电感与电容值满足系统运行要求,可以实现双向DC/DC变换器的快速响应,能够快速控制电流值,并获得稳定的电压参数,能够满足优异的动态调控性能。

基于参数自整定模糊PID的BLDC控制研究

为解决传统PID控制在无刷直流电机调速系统中的控制精度低、效果不佳等问题,设计了一种基于参数自整定模糊PID控制的调速系统。通过在Matlab/Simulink仿真软件中建立了无刷直流调速系统的模型,分别采用传统PID控制、模糊PID控制和参数自整定模糊PID控制来对转速环进行调控,而电流环则采用PID控制。通过对比研究结果发现,采用参数自整定模糊PID控制的调速系统具有许多优势。系统的超调量较小,控制效果较好,同时提高了系统的鲁棒性。通过搭建模型并进行仿真实验,证明了采用参数自整定模糊PID控制的调速系统在解决无刷直流电机调速系统控制精度低、效果不佳等问题方面具有优势。这一方法能够有效提升系统的控制性能,并增强系统的鲁棒性。该无刷直流电机的调速系统可以稳定、可靠运行,满足使用需求。

Fault Tolerant Neuro-Robust Position Control of DC Motors

DC motors are widely used in industry such as mechanics, robotics, and aerospace engineering. In this paper, we present a high performance control method for position control of DC motors. Fault-tolerant control model are also addressed to combine with neuro-robust control approach. It is shown that with the proposed control algorithms, external disturbances and coupled dynamics inherent in the system are effectively compensated using neural network unit in which no analytical estimation on the upper bound of the reconstruction error and uncertainties is needed. Simulations on various flight conditions also confirm the effectiveness of the proposed methods.

Type-2 Fuzzy Logic Controllers Based Genetic Algorithm for the Position Control of DC Motor

Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.

基于ANF的共直流母线OW-PMSM低次谐波抑制研究

针对共直流母线开绕组永磁同步电机(OW-PMSM)非线性因素引起的低次谐波,采用基于最小均方(LMS)算法的自适应陷波器(ANF)对系统中3次、5次、7次谐波进行抑制。首先,分析了OW-PMSM中低次谐波产生的机理;然后,借助Matlab/Simulink探讨了120°解耦调制策略消除逆变器侧调制引起的零序电流,研究了ANF提取系统中相应频次的谐波,将提取的电流谐波补偿到电流环中;再次,抑制了由非线性因素等引起的低次谐波;最后,仿真及试验结果表明,采用ANF后系统中3次、5次、7次谐波含量明显降低。

Fault detection and diagnosis of permanent-magnetic DC motors based on current analysis and BP neural networks

In order to guarantee quality during mass serial production of motors, a convenient approach on how to detect and diagnose the faults of a permanent-magnetic DC motor based on armature current analysis and BP neural networks was presented in this paper. The fault feature vector was directly established by analyzing the armature current. Fault features were extracted from the current using various signal processing methods including Fourier analysis, wavelet analysis and statistical methods. Then an advanced BP neural network was used to finish decision-making and separate fault patterns. Finally, the accuracy of the method in this paper was verified by analyzing the mechanism of faults theoretically. The consistency between the experimental results and the theoretical analysis shows that four kinds of representative faults of low power permanent-magnetic DC motors can be diagnosed conveniently by this method. These four faults are brush fray, open circuit of components, open weld of components and short circuit between armature coils. This method needs fewer hardware instruments than the conventional method and whole procedures can be accomplished by several software packages developed in this paper.

A neural network-based commutation optimization strategy and drive system design for brushless DC motor

An optimized commutation method based on backpropagation(BP)neural network is proposed to resolve the low stability and high-power consumption caused by inaccurate commutation point prediction in conventional commutation strategy during acceleration and deceleration.This article also builds a complete brushless DC motor drive system based on the GD32F103 micro control unit(MCU),with an Artix-7 XC7A35T field programmable gate array(FPGA)to meet the performance requirements of neural network calculation for real-time motor commutation control.Experimental results show that the proposed optimization strategy can effectively improve the system stability during system acceleration and deceleration,and reduce the current spikes generated during speed chan-ges.The system power consumption is reduced by about 11.7%on average.

基于田口法多目标优化BLDCM

为了解决高效多目标优化电机输出性能的问题,采用田口法优化算法,以BLDCM为例,以初始设计参数为基础,按电机的输出转矩、转矩脉动和铁损作为待优化性能指标,设计了优化目标函数。将定子内径、槽深、槽开口、齿宽和气隙等关键结构参数设为优化变量,设计了正交试验,通过计算信噪比响应值并结合敏感性分析,筛选出稳定且满足设计要求的参数组合,确定最优的优化参数方案。针对优化前后的目标参数变化用有限元进行分析,证明该方法的合理性。

Analysis of torque-current characteristic of brushless DC motor driven by three-phase H-bridge

Presents the simulation and analysis of the steady state characteristic of a brushless DC motor studies the torque current characteristic of the motor as well and discusses the design of a current measure circuit for torque controlling.

基于CNN-A-BiLSTM的无刷直流电机故障诊断方法研究

无刷直流电机是大型设备重要的动力装置之一,电机的运行状态与设备的运行状态高度一致;但当前现有的电机故障诊断方法难以在多电机或存在电磁干扰的环境下对电机做出准确的状态判断;为了实现复杂环境的无刷直流电机状态诊断,研究融合了卷积神经网络算法和长短期记忆网络算法;研究通过长短期记忆网络算法的双向传播捕捉复杂环境对电机的影响特征,从而提高模型的诊断精准度;实验结果表明,提出模型在机电设备故障诊断数据集上的平均收敛时间为8.91 min,在电机故障数据集上的平均收敛时间为12.66 min,收敛时间均低于同组对照模型;其次提出模型的F_(1)值为94.17%,比对照模型分别高出4.87%和7.46%;此外,在对电机故障前后电压检测情况对比中,提出模型对电机故障发生时的检测结果更为详细;根据实验结果可以得出,研究提出的电机诊断模型具有优秀的性能,满足电机诊断行业的精准度需求。

开绕组BLDCM直接转矩控制电压矢量特性研究

基于直接转矩控制(DTC)的开绕组无刷直流电机(BLDCM)具有运行效率高、电压矢量多样、控制结构简单等优点,适用于工业领域。根据共直流母线开绕组BLDCM控制拓扑搭建了相应的数学模型,对该拓扑下电压矢量的特性进行理论分析及分类,并将电压幅值不为零的电压矢量分为大、中、小三类。分析结果表明:在相同的运行条件下,大矢量作用下转矩变化率最大,小矢量作用下转矩变化率最小,中矢量居于两者之间。仿真结果验证了理论分析的正确性和控制方法的可行性。

A Model-Based Unmatched Disturbance Rejection Control Approach for Speed Regulation of a Converter-Driven DC Motor Using Output-Feedback

The speed regulation problem with only speed measurement is investigated in this paper for a permanent magnet direct current(DC)motor driven by a buck converter.By lumping all unknown matched/unmatched disturbances and uncertainties together,the traditional active disturbance rejection control(ADRC)approach provides an intuitive solution for the problem under consideration.However,for such a higher-order disturbed system,the increase of poles for the extended state observer(ESO)therein will lead to drastically growth of observer gains,which causes severe noise amplification.This paper aims to propose a new model-based disturbance rejection controller for the converter-driven DC motor system using output-feedback.Instead of estimating lumped disturbances directly,a new observer is constructed to estimate the desired steady state of control signal as well as errors between the real states and their desired steady-state responses.Thereafter,a controller with only speed measurement is proposed by utilizing the estimates.The performance of the proposed method is tested through experiments on dSPACE.It is further shown via numerical calculations and experimental results that the poles of the observer within the proposed control approach can be largely increased without significantly increasing magnitude of the observer gains.

Power Factor Improvement of AC-DC Converter Based on Separately Excited DC Motor Using Passive Filter

In industries DC motor drives are very essential due to their high performance applications such as its reliability, ease of control, low cost and simplicity. And speed control of these motors is very easy due to power electronic AC-DC converters. These power electronic converters are with prominent low power factor and higher Total Harmonic Distortion (THD). These converters operate only for short time resulting non-sinusoidal waveform. This problem of harmonic distortion can be mitigated by reshaping the non-sinusoidal waveform to pure sine wave. Different wave shaping techniques have been developed by using different filters among which one is tuned passive filter. This paper proposed power factor improvement and harmonic mitigation of AC-DC converters based on separately excited DC motor using tuned passive filter. In this context experimental model is designed and results are analyzed by power quality analyzer.

Sensorless Control of Four-Switch Inverter for Brushless DC Motor Drive and Its Simulation

The major function of this proposed research is to control the speed of the brushless DC motor with sensor less control for four-switch three phase inverter. This proposed system is simplified the topological structure of the conventional six-switch three phase inverter. In this proposed method, a new structure of four-switch three phase inverter [1] with reduced number of switches for system is introduced to reduce the mechanical commutation, switching losses that occur in the six-switch method. The proposed inverter fed brushless DC motor used in sensorless control schemes which is used for sensing positioning signals. To improve sensor less control performance, four-switch electronic commutation modes based proportional intergral controller scheme is implemented. In this four-switch three phase inverter reduction of switches, low cost control and saving of hall sensor were incorporated. The feasibility of the proposed sensor less control four-switch three phase inverter fed brushless DC motor drive is implemented, analysed using MATLAB/SIMULINK, effective simulation results have been validated out successfully.

Steady-State Performance Analysis of Brushless DC Propulsion Motor

The brushless DC motor can be used in the marine electric propulsion system for its excellent control characteristics and large thrust. In order to estimate the operating performances of the brushless DC motor for the high-power shipping during the design stage, the steady-state analysis is as important as the dynamic analysis generally. A mathematical model of the brushless DC propulsion motor is established according to the state-space method for the dynamic and steady-state performance analysis. The state-space mathematical model is a set of linear differential equations, so the steady-state currents of the armature windings can be gained directly by the symmetrical boundary conditions and the eigenvalues of the system matrix. The steady-state simulation results are compared with the dynamic ones to validate the correctness of this eigenvector method.

Simulation Research of Fault Model of Detecting Rotor Dynamic Eccentricity in Brushless DC Motor Based on Motor Current Signature Analysis

基于Ansoft／Maxwell设置动态偏心故障，建立求解电机电感和磁链的有限元模型，通过仿真，证明了将感应电机动态偏心故障的特征频率经过简化后，同样适用于无刷直流电动机。基于Ansoft／Simplorer建立无刷直流电动机系统的仿真模型。在电机稳态运行下，对定子电流进行傅里叶分析，研究并建立基于定子电流监测动态偏心故障的仿真模型：动态偏心故障与特征频率的关系、动态偏心故障程度与特征频率幅值的关系。进而研究了无刷直流电动机稳态运行时转速波动对偏心故障监测的影响。仿真结果表明，转子偏心程度加大，特征频率的幅值增加。