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MRAS的异步电机无速度传感器的矢量控制

由于电机定转子参数的变化,利用一般的转子磁链对转速进行估算,将导致不能得到准确的结果。这里采用积分型转子磁链的参考和可调模型构建出一个基于MRAS的异步电机无速度传感器的矢量控制模型。该模型提高了矢量控制系统的动态性能并利用MATLAB,sIMULINK进行了异步电机无速度传感器矢量控制系统的仿真,验证了文中所采用的模型参考自适应的速度估算方法的可行性以及对参数误差的鲁棒性。     

A high-performance sensorless indirect stator flux orientation control of induction motor drive

A new method for the implementation of a sensorless indirect stator-flux-oriented control (ISFOC) of induction motor drives with stator resistance tuning is proposed in this paper. The proposed method for the estimation of speed and stator resistance is based only on measurement of stator currents. The error of the measured q-axis current from its reference value feeds the proportional plus integral (PI) controller, the output of which is the estimated slip frequency. It is subtracted from the synchronous angular frequency, which is obtained from the output integral plus proportional (IP) rotor speed controller, to have the estimated rotor speed. For current regulation, this paper proposes a conventional PI controller with feedforward compensation terms in the synchronous frame. Owing to its advantages, an IP controller is used for rotor speed regulation. Stator resistance updating is based on the measured and reference d-axis stator current of an induction motor on d-q frame synchronously rotating with the stator flux vector. Experimental results for a 3-kW induction motor are presented and analyzed by using a dSpace system with DS1102 controller board based on the digital signal processor (DSP) TMS320C31. Digital simulation and experimental results are presented to show the improvement in performance of the proposed method.     

New observer-based DFO scheme for speed sensorless field-orienteddrives for low-zero-speed operation

This paper describes a new direct field orientation (DFO) scheme based on a modified flux observer using measured stator voltages and currents. The proposed approach addresses the problem of torque control of speed sensorless drives at low-zero speed, where rapid speed changes do not occur and signal frequency can approach zero. The scheme can maintain field orientation and stable torque control with simultaneous resistance and speed tuning taking place. Simulations and locked rotor experiments with torque measurements are used for verification     

Online rotor resistance estimation using the transient state underthe speed sensorless control of induction motor

In the speed sensorless control of the induction motor, the machine parameters (especially rotor resistance R₂) have a strong influence on the speed estimation. It is known that the simultaneous estimation of the rotor speed and R₂ is impossible in the slip frequency type vector control, because the rotor flux is constant. But the rotor flux is not always constant in the speed transient state. In this paper, the R₂ estimation in the transient state without signal injection to the stator current is proposed. This algorithm uses the least mean square algorithm and the adaptive algorithm, and it is possible to estimate R₂ exactly. This algorithm is verified by the digital simulations and experiments     

Speed sensorless stator flux-oriented control of induction machine in the field weakening region

In a conventional speed sensorless stator flux-oriented (SFO) induction machine drive system, when the estimated speed is transformed into the sampled-data model using the first-forward difference approximation, a modeling error occurs in the sampled data model. As the result, an error in the rotor speed estimation is produced. The error included in sampled data model of the estimated speed is removed by the use of a digital low pass filter (LPF). However, the delay of the estimated speed occurs in transients due to the use of the LPF. Consequently, current control loss occurs at the transition to field weakening region by the delay of the estimated speed. This paper investigates the problem of a conventional speed sensorless SFO system produced by the delay of the estimated speed in the field weakening region. In addition, this paper proposes a new method to estimate exactly rotor speed by using a Kalman filter. The proposed method is verified by simulation and experiment.     

基于Matlab／Simuljnk的无速度传感器直接转矩控制的仿真

本文介绍了异步电动机直接转矩控制的基本原理，提出了基于自适应全阶磁链观测器的速度估算方法，实现了无速度传感器的速度辨识。并应用Matlab／Simulink软件对该系统进行了建模和仿真，仿真结果表明，该系统对电机定子磁链的观测精度高，转速估算准确，尤其在低速下能保持很高的性能。     

A sensorless vector control system for induction motors usingq-axis flux with stator resistance identification

This paper presents a sensorless vector control system for general-purpose induction motors, which is based on the observer theory and the adaptive control theories. The proposed system includes a rotor speed estimator using a q-axis flux and stator resistance identifier using the d-axis flux. The advantages of the proposed system are simplicity and avoidance of problems caused by using only a voltage model. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including the influence of the observer gain, motor operating state, and parameter variations. In order to obtain stable low-speed operation and speed control accuracy, an algorithm for compensating for the deadtime of the inverter and correcting the nonideal features of an insulated gate bipolar transistor was developed. The effectiveness of the proposed system has been verified by digital simulation and experimentation     

A MRAS-based adaptive pseudoreduced-order flux observer for sensorless induction motor drives

The performance of vector-controlled sensorless induction motor drives is generally poor at very low speeds, especially at zero speed due to offset and drift components in the acquired feedback signals, and the increased sensitivity of dynamic performance to model parameter mismatch resulting especially from stator resistance variations. The speed estimation is adversely affected by stator resistance variations due to temperature and frequency changes. This is particularly significant at very low speeds where the calculated flux deviates from its set values. Therefore, it is necessary to compensate for the parameter variation in sensorless induction motor drives, particularly at very low speeds. This paper presents a novel method of estimating both the shaft speed and stator resistance of an induction motor. In this novel scheme, an adaptive pseudoreduced-order flux observer (APFO) is developed. In comparison to the adaptive full-order flux observer (AFFO), the proposed method consumes less computational time, and provides a better stator resistance estimation dynamic performance. Both simulation and experimental results confirm the superiority of the proposed APFO scheme for a wide range of resistance variations from 0 to 100%.     

Speed sensorless stator flux-oriented control of induction motor in the field weakening region using Luenberger observer

In a conventional speed sensorless stator flux-oriented (SFO) induction motor drive, when the estimated speed is transformed into the sampled-data model using the first-forward difference approximation, the sampled-data model has a modeling error which, in turn, produces an error in the rotor speed estimation. The error included in the estimated speed is removed by the use of a low pass filter (LPF). As the result, the delay of the estimated speed occurs in transients by the use of the LPF. This paper investigates the problem of a conventional speed sensorless SFO system due to the delay of the estimated speed in the field weakening region. In addition, this paper proposes a method to estimate exactly speed by using Luenberger observer. The proposed method is verified by the simulation and experiment with a 5-hp induction motor drive.     

Stator resistance tuning in a stator-flux field-oriented driveusing an instantaneous hybrid flux estimator

A self-tuning control scheme for stator-flux field-oriented induction machine drives in electric vehicles operating over a wide speed range is discussed in this paper. The stator flux can be determined accurately from the terminal voltage when the machine is operating at high speed. However, at low speed, the stator resistance must be known to calculate the stator flux. The problem of calculating the stator flux accurately over the entire speed range is addressed. The rotor flux can be found from the machine speed and rotor time constant. The stator flux, at low speed, is then calculated directly from the rotor flux. By alternating between these two methods of determining the stator flux, a self-tuning operation is achieved, wherein the stator and rotor resistances are periodically updated. Since both methods of determining the stator flux are forced to track one another, a smooth transition between flux estimators is obtained. The torque and flux are then controlled in a deadbeat fashion. Good torque control over a wide speed range can therefore be obtained. With the proposed scheme, the advantages of direct torque control are obtained over the entire speed range with the addition of a speed sensor     

Sensorless double-inverter-fed wound-rotor induction-Machine drive

The basic operation of a wound-rotor induction-motor drive fed by inverters on the stator as well as the rotor side is discussed. Different modes of operations are defined and explained based on power flow on both the sides of the machine. The sensorless motor control scheme consists of V/f-type direct frequency control on one side, with either vector control or direct torque and flux control on the other side. The machine operates up to twice the rated speed in either direction, with full flux and torque, thereby producing up to twice the rated power. Novel frequency profiles are proposed, which ensure that the frequency on either side never drops below a minimum value (set at 12 Hz in this work). Therefore, the estimation of flux can be simply and reliably carried out by integration of voltage, resulting in simple sensorless control. The drive works reliably at all speeds including zero speed and at all loads. Results from a 50-hp prototype drive are presented.     

Experimental Evaluation of Braided EKF for Sensorless Control of Induction Motors

Temperature- and frequency-dependent variations of the rotor (R'_r) and stator (R_s) resistances pose a challenge in the accurate estimation of flux and velocity in the sensorless control of induction motors (IMs) over a wide speed range. Solutions have been sought to the problem by signal injection and/or by the use of different algorithms for the different parameters and states of the same motor. In this paper, a novel Extended-Kalman-Filter (EKF)-based estimation technique is developed for the solution of the problem based on the consecutive operation of two EKF algorithms at every time step. The proposed ldquobraidedrdquo EKF technique is experimentally tested under challenging parameter and load variations in a wide speed range, including low speed. The results demonstrate a significantly increased accuracy in the estimation of R_s and R'_r, as well as load torque, flux, and velocity in transient and steady state, when compared with single EKFs or other approaches taken to estimate these parameters and states in the sensorless control of IMs. The improved results also motivate the utilization of the new estimation approach in combination with a variety of control methods which depend on accurate knowledge of a high number of parameters and states.     

Speed-sensorless sliding-mode torque control of an induction motor

Novel induction motor control optimizing both torque response and efficiency is proposed in the paper. The main contribution of the paper is a new structure of rotor flux observer aimed at the speed-sensorless operation of an induction machine servo drive at both low and high speed, where rapid speed changes can occur. The control differs from the conventional field-oriented control. Stator and rotor flux in stator fixed coordinates are controlled instead of the stator current components in rotor field coordinates i_sd and i_sq. In principle, the proposed method is based on driving the stator flux toward the reference stator flux vector defined by the input command, which are the reference torque and the reference rotor flux. The magnitude and orientation angle of the rotor flux of the induction motor are determined by the output of the closed-loop rotor flux observer based on sliding-mode control and Lyapunov theory. Simulations and experimental tests are provided to evaluate the consistency and performance of the proposed control technique     

Sensorless control of salient PMSM with adaptive integrator and resistance online identification using strong tracking filter

This article presents a sensorless control approach of salient PMSM with an online parameter identifier. Adaptive Integrator is proposed and utilised for the estimation of active flux and rotor position. As a result, integrator overflow caused by DC offset is avoided. Meanwhile, an online stator resistance identification algorithm using strong tracking filter is employed, and the identified stator resistance is fed back to the estimating algorithm. Thus, the estimating algorithm can calculate the rotor position correctly. Simulations and experimental results validate the feasibility of both adaptive integrator and the parameter identification method.     

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。     

An improved stator flux estimation for speed sensorless stator fluxorientation control of induction motors

This paper proposes a programmable low pass filter (LPF) to estimate stator flux for speed sensorless stator flux orientation control of induction motors. The programmable LPF is developed to solve the DC drift problem associated with a pure integrator and a LPF. The pole of the programmable LPF is located far from the origin in order to decrease the time constant with the increasing speed. In addition, the programmable LPF has a phase/gain compensator to estimate exactly stator flux in a wide speed range. Consequently, the drift problem is much improved and the stator flux is exactly estimated in the wide speed range. The validity of the proposed programmable LPF is verified by speed sensorless vector control of a 2.2 kW three-phase induction motor     

Sensorless field orientation control of induction machines based ona mutual MRAS scheme

A mutual model reference adaptive system (MRAS) is proposed to implement a position sensorless field-orientation control (FOC) of an induction machine. The reference model and adjustable model used in the mutual MRAS scheme are interchangeable. Therefore, it can be used to identify both rotor speed and the stator resistance of an induction machine. For the rotor speed estimation, one model is used as a reference model and another is the adjustable model. Pure integration and stator leakage inductance are removed from the reference model, resulting in robust performance in low and high speed ranges. For the stator resistance identification, the two models switch their roles. To further improve estimation accuracy of the rotor speed and stator resistance, a simple on-line rotor time constant identification is included. Computer simulations and experimental results are given to show its effectiveness     

Flux observer with online tuning of stator and rotor resistancesfor induction motors

This paper proposes an adaptive flux observer for induction motors, where stator and rotor resistances are estimated in online environments. The variation of motor parameters during operation degrades the performance of the controller and the flux observer. Among the parameters of induction motors, rotor resistance is a crucial one for flux estimation, and stator resistance also becomes critical in the low-speed region. Under the persistent excitation condition, the proposed method estimates the actual values of stator and rotor resistances simultaneously, which guarantees the exact estimation of the rotor flux. The persistent excitation condition is not satisfied when the electric torque of an induction motor is absent due to the lack of rotor currents. Even in this case, the proposed method achieves the correct estimation of the rotor flux. Simulations and actual experiments show that the rotor flux is estimated in all operating conditions and that both resistances converge to their actual values when the electrical motor torque exists     

An improved DTC-SVM method for matrix converter drives using a deadbeat scheme

In this paper, a simple direct torque control (DTC) method for sensorless matrix converter drives is proposed, which is characterized by a simple structure, minimal torque ripple and unity input power factor. Also, a good sensorless speed-control performance in the low speed operation is obtained, while maintaining constant switching frequency and fast torque dynamics. It is possible to combine the advantages of matrix converters with the advantages of the DTC strategy using space vector modulation a deadbeat algorithm in the stator flux reference frame. Experimental results are shown to illustrate the feasibility of the proposed strategy.