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.     

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.     

An improved flux observer based on PLL frequency estimator for sensorless vector control of induction motors

This paper presents an improved method of flux estimation for sensorless vector control of induction motors based on a phase locked loop (PLL) programmable low-pass filter (LPF) and a vector rotator. A PLL synchronized with the voltage vector is used for stator frequency estimation. The pure integration of the stator voltage equations is difficult to implement and LPFs with a fixed cutoff provide good estimates only in the relatively high frequency range-at low frequencies, the estimates fail in both magnitude and phase. The method proposed corrects the above problem for a wide range of speeds. Simulations and experimental results on a 0.25-hp three-phase induction machine verify the validity of the approach.     

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%.     

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.     

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     

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     

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.     

On Sensorless Induction Motor Drives: Sliding-Mode Observer and Output Feedback Controller

In this paper, a sensorless output feedback controller is designed in order to drive the induction motor (IM) without the use of flux and speed sensors. First, a new sliding-mode observer that uses only the measured stator currents is synthesized to estimate the speed, flux, and load torque. Second, a current-based field-oriented sliding-mode control is developed so as to steer the estimated speed and flux magnitude to the desired references. A stability analysis based on the Lyapunov theory is also presented in order to guarantee the closed-loop stability of the proposed observer-control system. Two experimental results for a 1.5-kW IM are presented and analyzed by taking into account the unobservability phenomena of the sensorless IM.      

A new scheme for speed-sensorless control of induction motor

Various control algorithms have been proposed for the speed-sensorless control of an induction motor. These sensorless algorithms are mainly based on the speed feedback with the flux and speed estimations. This paper proposes a new scheme for the speed-sensorless control of an induction motor. The proposed scheme is based on the current estimation without the flux and speed estimations, in which the controlled stator voltage is applied to the induction motor so that the difference between stator currents of the mathematical model and motor may be forced to decay to zero. The performance of the proposed scheme is verified through 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。     

Control strategies for power smoothing using a flywheel driven by a sensorless vector-controlled induction machine operating in a wide speed range

This paper presents a novel control strategy for power smoothing. The system is based on a sensorless vector-controlled induction machine driving a flywheel. The problem of regulating the DC-link voltage against input power surges or sudden changes in load demand is addressed. The induction machine is controlled to operate in a wide speed range by using flux weakening above rated speed. A model reference adaptive system observer is used to obtain the rotational speed in the whole speed range. The observer parameters are adapted during flux weakening in order to obtain close tracking of the flywheel speed. Experimental results for the operation of the induction machine between zero to more than twice base speed are presented and discussed.     

Stator flux based space-vector modulation and closed loop control of the stator flux vector in overmodulation into six-step mode

This paper presents closed loop control of stator flux vector in a wide operating range that can be used in torque control. A predictive control achieves zero phase error at constant switching frequency. Space vector modulation based on stator flux error vector is used to achieve control of stator flux over the entire range including overmodulation and six-step. During dynamics the fastest possible flux vector change is employed similar to the direct torque control. Experimental results are provided for a wide speed range and effect of parameter variation is studied.     

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 self-tuning closed-loop flux observer for sensorless torquecontrol of standard induction machines

This paper proposes a self-tuning closed-loop flux observer, which provides field-oriented torque control for induction machines without a tachometer. The proposed algorithm combines the best features of harmonic detection and stator voltage integration through the use of a new tuning scheme. The observer accuracy and robustness is augmented by a parameter-independent accurate-speed detector, which analyzes magnetic saliency harmonics in the stator current. The harmonic-detection scheme provides accurate rotor-speed updates during steady-state operation down to 1-Hz source frequency. This additional speed information is used to tune the rotor-resistance parameter of the observer. The tuned observer exhibits improved dynamic performance, accurate steady-state speed control and an extended range of control near zero speed. The algorithm requires no special machine modifications and can be implemented on most existing low- and medium-performance drives. The closed-loop nature of the flux observer, combined with the harmonic-detection scheme, provides flux and speed error feedback, which significantly increases the robustness of sensorless control across the entire speed range     

An implementation of a programmable cascaded low-pass filter for a rotor flux synthesizer for an induction motor drive

This paper investigates a programmable cascaded low pass filter for the estimation of rotor flux of an induction motor, with a view to estimate the rotor time constant of an indirect field orientation controlled induction motor drive. Programmable cascaded low pass filters have been traditionally used in stator flux oriented vector control of the induction motor. This paper extends the use of this filter to estimate the rotor flux for the indirect field orientation control by generating rotor flux estimates from stator flux estimates. This is achieved by using a three-stage programmable cascaded low pass filter. The three-stage programmable cascaded low-pass filter investigated in this paper has resulted in excellent estimation of rotor flux in the steady-state and transient operation of an indirect field oriented drive. The estimated rotor flux data have also been used for the on-line rotor resistance identification with artificial neural network. Modeling and experiment results presented in this paper demonstrate this method of estimating rotor flux clearly.     

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。     

基于自适应状态观测器的异步电机无速度传感器矢量控制系统

异步电机无速度传感器矢量控制系统是目前研究的热点,本文采用一种闭环磁链观测器,即自适应状态观测器对转子磁链进行观测,与传统开环电压、电流模型相比,观测效果更好。在转子磁链观测的基础上,采用PI型自适应律,对转速进行了辨识。最后,通过Matlab仿真验证了本文给出的异步电机无速度传感器矢量控制系统的可行性,仿真结果表明该系统具有较好的动、静态性能,并具有一定的抗干扰能力。     

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     

Sensorless speed measurement using current harmonic spectralestimation in induction machine drives

This paper proposes a sensorless speed measurement scheme that improves the performance of transducerless induction machine drives, especially for low-frequency operation. Speed-related harmonics that arise from rotor slotting and eccentricity are analyzed using digital signal processing. These current harmonics exist at any nonzero speed and are independent of time-varying parameters, such as stator winding resistance. A spectral estimation technique combines multiple current harmonics to determine the rotor speed with more accuracy and less sensitivity to noise than analog filtering methods or the fast Fourier transform. An on-line initialization routine determines machine-specific parameters required for slot harmonic calculations. This speed detector, which has been verified at frequencies as low as 1 Hz, can provide robust, parameter-independent information for parameter tuning or as an input to a sensorless flux observer for a field-oriented drive. The performance of the algorithm is demonstrated over a wide range of inverter frequencies and load conditions