Model Reference Adaptive System Against Rotor Resistance Variation in Induction Motor Drive

The paper deals with a compensation method of the rotor-resistance variation in induction motor drives using high-performance slip-frequency control. Our proposed method is based on a discrete-type model reference adaptive system (MRAS), and it is implemented in an 8086 microprocessor. When an induction motor is driven by a controlled current source, the system sensitivity to the rotor resistance variation is increased. In the MRAS, the value of the rotor resistance is estimated and the slip-frequency gain is adjusted. Experimental and numerical results show that even if the value of the rotor resistance varies from its nominal value, the secondary flux level is maintained constant by using this compensation method. These results point out the validity of our proposed method.     

Online Stator and Rotor Resistance Estimation Scheme Using Artificial Neural Networks for Vector Controlled Speed Sensorless Induction Motor Drive

This paper presents a new method of online estimation for the stator and rotor resistances of the induction motor for speed sensorless indirect vector controlled drives, using artificial neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The rotor speed is synthesized from the induction motor state equations. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, are investigated with the help of simulations for variations in the stator and rotor resistances from their nominal values. Both resistances are estimated experimentally, using the proposed neural network in a vector controlled induction motor drive. Data on tracking performances of these estimators are presented. With this speed sensorless approach, the rotor resistance estimation was made insensitive to the stator resistance variations both in simulation and experiment. The accuracy of the estimated speed achieved experimentally, without the speed sensor clearly demonstrates the reliable and high-performance operation of the drive     

基于模型参考自适应系统的感应电机控制

采用模型参考自适应法设计了无速度传感器矢量观测器。现以电压模型为参考模型,电流模型为可调模型,推算出速度信息,计算输出控制信号,实现了对感应电机的精确控制;通过Matlab／Simulink对其进行仿真、验证,结果表明,该系统对定子磁链观测精度高,速度估计准确,改善了电机的控制特性。     

FPGA-Based Adaptive Backstepping Sliding-Mode Control for Linear Induction Motor Drive

A field-programmable gate array (FPGA)-based adaptive backstepping sliding-mode controller is proposed to control the mover position of a linear induction motor (LIM) drive to compensate for the uncertainties including the friction force. First, the dynamic model of an indirect field-oriented LIM drive is derived. Next, a backstepping sliding-mode approach is designed to compensate the uncertainties occurring in the motion control system. Moreover, the uncertainties are lumped and the upper bound of the lumped uncertainty is necessary in the design of the backstepping sliding-mode controller. However, the upper bound of the lumped uncertainty is difficult to obtain in advance of practical applications. Therefore, an adaptive law is derived to adapt the value of the lumped uncertainty in real time, and an adaptive backstepping sliding-mode control law is the result. Then, an FPGA chip is adopted to implement the indirect field-oriented mechanism and the developed control algorithms for possible low-cost and high-performance industrial applications. The effectiveness of the proposed control scheme is verified by some experimental results. With the adaptive backstepping sliding-mode controller, the mover position of the FPGA-based LIM drive possesses the advantages of good transient control performance and robustness to uncertainties in the tracking of periodic reference trajectories.     

异步电机无速度传感器矢量控制系统研究

根据模型参考自适应方法对异步电机转子转速进行辨识,结合应用SVPWM技术,构建了无速度传感器矢量控制系统。利用Matlab/Simulink对该系统进行了计算机仿真,仿真结果表明其对异步电机转子速度的估算具有较高的准确性,所设计的控制系统具有良好的动态性能。     

Using an Artificial Neural Network as a Rotor Resistance Estimator in the Indirect Vector Control of an Induction Motor

This paper presents a rotor resistance estimator based on an artificial neural network (ANN) used in the indirect vector control (IVC) of an induction motor (IM). Attention is focused on the dynamic performance of ANN rotor estimator, which gives superior performance over the fuzzy logic based rotor estimator reported in technical literature. The simulation was done using a 1.5 HP induction motor. The same ANN rotor estimator was proved with other IM having different rated power. The use of the same ANN was possible because the scaling and descaling (normalization) of the input and output of ANN was property done for each motor. The ANN training was done offline using the Levenberg-Marquardt algorithm. The neuronal network is a three-layer network; the first layer has fourteen neurons (or nodes), the hidden layer has five neurons and the output layer has only one neuron because the unique output signal is the rotor resistance value.     

交流电机变频调速讲座第七讲按转子磁链定向的异步电动机矢量控制系统

前讲表明,异步电动机的动态数学模型是一个高阶、非线性、强耦合的多变量系统,虽然通过坐标变换,可以使之降阶并化简,但并没有改变其非线性、多变量的本质。因此,需要异步电动机调速系统具有高动态性能时,必须面向这样一个动态模型的难题。经过许多学者的潜心研究和实践,首先获得成功和应用的是按转子磁链定向的矢量控制系统。     

感应电机矢量控制与直接转矩控制系统的低速性能对比

本文详细分析了感应电机矢量控制和直接转矩控制系统的基本原理。在此基础上,基于matlab6.5／simulink分别建立了基于转子磁场定向的矢量控制系统和基于U—I模型的直接转矩控制系统的仿真模型。仿真研究了定子电阻、转于电阻变化对这两种控制系统低速性能的影响。并进行了对比分析。仿真结果表明,直接转矩控制系统具有更快的转矩响应,转子电阻对矢量控制系统影响较大,而定子电阻对基于U—I模型的直接转矩控制系统的影响较大。     

A Novel Polygon Based 18-Pulse AC–DC Converter for Vector Controlled Induction Motor Drives

This paper presents a novel configuration of an autotransformer based 18-pulse ac-dc converter for improving the power quality at the point of common coupling (PCC) in variable frequency induction motor drives (VFIMDs). The polygon based connection of autotransformer for achieving 18-pulse rectification is utilized to result in reduction in rating of the magnetics. The design of the autotransformer is carried out for an 18-pulse ac-dc converter feeding a vector controlled induction motor drive (VCIMD). Moreover, the autotransformer design is modified for making it suitable for retrofit applications, where presently a 6-pulse diode bridge rectifier is used. The effect of load variation on VCIMD is also studied and the performance of the proposed 18-pulse ac-dc converter is compared in terms of different power quality indices on both ac as well as dc side with other ac-dc converters. A laboratory prototype of the proposed autotransformer based 18-pulse ac-dc converter feeding a 10-hp induction motor drive is developed to verify the design and simulated results     

风电并网逆变器用有无功功率解耦控制的矢量控制策略

三相PWM逆变器是风力发电并网系统的主要部分,开发一种高性能的逆变器控制策略已经成为研究的重点。本文在对风力发电并网逆变器系统数学模型分析的基础上,提出了一种改进的矢量控制策略。它主要由两个双环控制模型构成,分别都是电流外环电压内环的结构。通过实时检测并网电流和电网电压的波动,有效的补偿并网电感的电压信号,就能够很好的补偿逆变器PWM调制波信号。本文提出的这种矢量控制结构不仅可以改善并网电流的波形质量,而且在系统给定参数发生变化的情况下,仍然可使系统具有很强的鲁棒性,此外,该结构还能有效补偿直流侧母线电压的脉动对并网电流质量的影响。     

高压变频调速技术及其在电厂中的应用

文章在简单分析了高压变频器技术特点的基础上,详细分析了影响高压变频器选用所必须考虑的技术因素,以及采用高压变频器的经济性。     

开关磁阻电机功率变换器杂散参数抑制及散热设计

功率变换器是开关磁阻电机调速系统(以下简称SRD)中保证电机可靠稳定运行的关键部件。在大功率功率变换器设计过程中,对电路的杂散参数以及功率器件的散热等问题的处理是功率变换器结构设计的关键。针对电路中的杂散参数,本文在设计功率变换器过程中构建了60KW开关磁阻电机功率变换器逆变回路杂散电感等效分布模型,分析了杂散电感在器件关断过程中的影响。在此基础上,引入低感叠层母线技术,从结构设计与工程运用角度出发对该母线进行分析,理论计算与仿真结果均表明设计方案比传统设计方案更有效地抑制了主回路杂散电感值。针对功率器件的散热问题,提出一种针对SRM负载的功率电路热损耗估算方法。通过损耗计算得出功率变换器主电路中损耗的来源和器件温升变化,对功率变换器的进一步设计改进有重要意义。     

火电厂循环泵电机双速改造及运行分析

通过对华电新疆发电有限公司苇湖梁电厂（以下简称苇电厂）125MW#2机组2-1循环泵电机双速调节改造前、后运行分析,论述改造为双速电机后,运行人员可以根据机组负荷和环境温度的变化,灵活地改变循环系统水泵的数量和转速,达到最有利真空的控制目的,从而改变了原循环水系统的工作状况,实现了汽轮机真空度高精度控制和经济运行,且投资少,效果显著。     

Heuristic and Statistical Power Estimation Model for FPGA Based Wireless Systems

Wireless Personal Communications - As the technology is advancing day by day, the need of high performance devices is also increasing. High performance is achieved at the expense of high power...     

Design and Implementation of a Robust Current-Control Scheme for a PMSM Vector Drive With a Simple Adaptive Disturbance Observer

This paper introduces a robust current-control scheme for a permanent-magnet synchronous motor (PMSM) with a simple adaptive disturbance observer. The robust controller is realized by including an adaptive element in the reference-voltage-generation stage using the feedforward control. Due to the time-varying nature and the high-bandwidth property of the uncertainties in a practical PMSM drive system, the adaptive element is simply chosen as the estimated uncertainty function, which adaptively varies with different operating conditions. Subsequently, the frequency modes of the uncertainty function are embedded in the control effort, and a robust current-control performance is yielded. Furthermore, the inclusion of the estimated uncertainty function provides an efficient solution for torque-ripple minimization in PMSM drives. This is because the frequency modes of the disturbances to be eliminated, i.e., the flux harmonics, are included in the stable closed-loop system. To provide a high-bandwidth estimate of the uncertainty function, a simple adaptation law is derived using the nominal current dynamics and the steepest descent method. To guarantee the system's convergence and to properly tune the proposed observer, a stability analysis based on a discrete-time Lyapunov function has been used. Comparative evaluation experiments are presented to demonstrate the effectiveness of the proposed control scheme under different operating conditions.     

Low-Dropout Regulators With Adaptive Reference Control and Dynamic Push–Pull Techniques for Enhancing Transient Performance

An adaptive reference control (ARC) technique is proposed for minimizing overshoot/undershoot voltage and settling time of low-dropout regulators. Linear operation provided by the ARC technique can dynamically and smoothly adjust the reference voltage so as to increase the slew rate of error amplifier thus forcing the output voltage back to its steady-state value rapidly. The amount of transient revision is proportional to transient state output voltage variation and load condition. In addition, a dynamic push-pull technique is used to enhance transient response. Experimental results demonstrate that the undershoot voltage, settling time, and load regulation are improved by 31%, 68.5%, and 70%, respectively, when load current changes between 1 and 100 mA.     

A Remote and Sensorless Stator Winding Resistance Estimation Method for Thermal Protection of Soft-Starter-Connected Induction Machines

This paper proposes a remote and sensorless stator winding resistance estimation method for thermal protection of soft-starter-connected induction motors. By changing the gate drive signals of the thyristors in the soft starter, a small adjustable dc bias can be intermittently injected to the motor for the estimation of the stator winding resistance. Based on online and continuous monitoring of the stator winding resistance, the stator winding temperature can be monitored using only motor voltage and current. In addition, the torque pulsation caused by the injected dc bias is analyzed. It can also be controlled under an acceptable level by adjusting the level of the injected dc signal. The influence of cable resistance is also studied, and a compensation method is proposed. The proposed method has been verified by experimental results from two induction motors. The proposed stator resistance estimation method can provide remote, sensorless, and accurate thermal protection for soft-starter-connected induction motors.     

基于P型功率管电流采样和自适应参考电压的Buck型充电器设计

介绍了一种具有高效率、开关频率为2 MHz的Buck型锂电池充电器,它的工作过程分为启动、小恒定电流充电、大恒定电流充电、恒定电压控制和结束五个阶段。在恒流充电阶段,通过对P型功率管电流的采样和采用自适应参考电压,可以对充电电流的平均值进行控制,使得充电电流恒定,不受电池电压升高的影响。在恒压控制阶段,附加一条电压反馈回路,使得恒流阶段到恒压阶段的转换平滑。本设计用2P4M 350nm CMOS工艺实现,芯片面积2.8mm2。测试结果表明,芯片实现了充电的完整过程,其充电峰值效率为91%。     

Adaptive Neural Fuzzy Inference System for the Detection of Inter-Turn Insulation and Bearing Wear Faults in Induction Motor

The positive features of neural networks and fuzzy logic are combined together for the detection of stator inter-turn insulation and bearing wear faults in single-phase induction motor. The adaptive neural fuzzy inference systems (ANFISs) are developed for the detection of these two faults. These faults are created experimentally on a single-phase induction motor in the laboratory. The experimental data is generated for the five measurable parameters, viz, motor intakes current, speed, winding temperature, bearing temperature, and the noise of the machine. Earlier, the ANFIS fault detectors are trained for the two input parameters, i.e., speed and current, and the performance is tested. Later, the three remaining parameters are added and the five input ANFIS fault detector is trained and tested. It observed from the simulation results that the five input parameter system predicts more accurate results     

Decoupling Capacitor Estimation and Allocation using Optimization Techniques for Power Supply Noise Reduction in System-on-Chip

Journal of Electronic Testing - This article examines the signal integrity problem arising due to resistive drop, inductive noise and electro- migration, causing voltage fluctuations known as...