Sensorless Control Of Induction Motor Research Articles

Design of a MRAS, Speed and Flux Estimators used in Sensorless Control of Induction Motors

Model reference adaptive system (MRAS) based techniques are one of the best methods to estimate the rotor speed. Speed and torque control of an induction motor is usually attained by application of a speed or position sensor. However, these require the additional mounting space, reduce the reliability and increase the cost of the motor. The recent trend in field oriented control (FOC) is towards the use of sensorless techniques that avert the use of speed sensor and flux sensor. This paper seeks to provide a direct comparison between two technics of induction motor MRAS based speed estimators, one based on the rotor flux and the other based on the back EMF. Comparison between the two techniques is made through computer simulations.

Model Reference Adaptive System Sensorless Vector Control of an Induction Motor Using a Novel Fractional Order PI Controller Adaptation Mechanism

Recently, speed sensorless control of Induction Motor (IM) drives received great attention to avoid the different problems associated with direct speed sensors. Among different rotor speed estimation techniques, Model Reference Adaptive System (MRAS) schemes are the most common strategies employed due to their relative simplicity and low computational effort. In this paper a novel adaptation mechanism is proposed which replaces normally used conventional Proportional-Integral (PI) controller in MRAS adaptation mechanism by a Fractional Order PI (FOPI) controller. The performance of two adaptation mechanism controllers has been verified through simulation results using MATLAB/SIMULINK software. It is seen that the performance of the induction motor has improved when FOPI controller is used in place of classical PI controller.

Convergence analysis of back-EMF MRAS observers used in sensorless control of induction motor drives

This paper seeks to analyse stability and dynamics of back EMF MRAS based approach used in sensorless control of induction motors. Stability analysis is investigated to show unstable zones and it is explored using a state representation. A new rotor speed estimator is designed to achieve the stability in the various operating modes except for the inobservability line.

Convergence Analysis of Extended Kalman Filter for Sensorless Control of Induction Motor

This paper deals with convergence analysis of the extended Kalman filters (EKFs) for sensorless motion control systems with induction motor (IM). An EKF is tuned according to a six-order discrete-time model of the IM, affected by system and measurement noises, obtained by applying a first-order Euler discretization to a six-order continuous-time model. Some properties of the discrete-time model have been explored. Among these properties, the observability property is relevant, which leads to conditions that can be directly linked with the working conditions of the machine. Starting from these properties, the convergence of the stochastic state estimation process, in mean square sense, has been shown. The convergence is also explored with reference to the difference between the samples of the state of the continuous-time model and that estimated by the EKF. The results theoretically achieved have been also validated by means of experimental tests carried out on an IM prototype.

Model Reference Adaptive System based Speed Sensorless Control of Induction Motor using Fuzzy-PI Controller

this paper a Model Reference Adaptive System (MRAS) is presented as the speed estimation technique in which the error speed is estimated by comparing reference model and adaptive model and further the error speed is used to obtain the rotor speed. Proportional Integral (PI) is designed for controlling purpose. A non-linear fuzzy-PI controller is used to optimize the speed error value. The Proposed MRAS based speed sensorless control of Induction Motor (IM) drive will ensure the better dynamic performance and reliability, compared to conventional methods. The proposed scheme is simulated using MATLAB/Simulink software. Keywordsspeed control, Model Reference Adaptive System (MRAS), Induction Motor, stationary reference frame, speed estimation.

A speed estimation of sensorless control for asymmetrical parameter type two-phase induction motor drives

This paper presents the concept of a speed estimation of sensorless control for asymmetrical parameter type two-phase induction motor drive, by using the adaptive observer system. The motor speed is estimated on the rotor-flux reference frame to simplicity for application. The design guideline of the gain of speed estimate system for a motor has speed change. The experimental results for all test conditions show that the responses of current, torque and speed are stable for the entire operating region.

Circle-criterion Based Nonlinear Observer Design for Sensorless Induction Motor Control

This paper deals with the design of a nonlinear observer for sensorless induction motor control. Based upon the circle criterion approach, a nonlinear observer is designed to estimate pertinent but unmeasurable state variables of the considered induction machine for sensorless control purpose. The observer gain matrices are computed as a solution of linear matrix inequalities (LMI) that ensure the stability conditions of the state observer error dynamics in the sense of Lyapunov concepts. Measured and estimated state variables can be exploited to perform a state feedback control of the machine system. The simulation results are presented to illustrate the effectiveness of the proposed approach for nonlinear observer design.

Direct Torque Control of Four Switch Three Phase Inverter fed Induction Motor Sensorless Speed Drive

This paper presents sensorless speed control of induction motor (IM) using four switch three phase inverter (FSTPI) with direct torque and flux control (DTFC). The proposed sensorless DTFC system consists of an adaptive observer of rotor flux to accurately estimate stator resistance and speed simultaneously, without affecting drive performances. The switching technique for DTFC of IM using FSTPI in low power application is based on the principle of similarity between FSTPI and SSTPI (six switch three phase inverter), where the αβ plan is divided into 6 sectors and the formation of the voltage space vector is done in the same way as for SSTPI by using effective (mean) vectors. This approach allows using the well-known established switching table of SSTPI for FSTPI. The simulation results indicates that the sensorless speed control of FSTPI fed IM with DTFC and adaptive observer provides accurate estimate, good trajectory tracking with different dynamics performance. The experimental results verify the effectiveness of the proposed method at different operating points. DOI: http://dx.doi.org/10.11591/ijpeds.v5i2.5645

Reduced Rule FLC for Sensorless Control of Induction Motor Drive

Reduced Rule FLC for Sensorless Control of Induction Motor Drive

English

This paper proposes the controlling of Induction motor drives.Because of low maintenance and robustness, induction motors have many applications in industries. Speed control of induction motor is more important to achieve maximum torque and efficiency. Various control techniques such as scalar control, vector control, Sensor-less control are used. These Schemes suffers from parameter sensitivity and limited performance at low speed of operation. Sensor-less control of induction motor drive using model reference adaptive system with PI controller as reference model will limit the performance at low speed of operation. In this thesis, a novel adaptation mechanism is proposed which replaces PI controller in MRAS adaptation mechanism by a fuzzy logic controller. This is applied to a vector controlled drive and experimentally verified. This makes the reference model free from pure integration and less sensitive to stator resistance variations. This improves the performance of MRAS based sensor-less drives at low speed of operation.

Development and Experimental Evaluation of a Sensorless Speed Control of SPIM Using Adaptive Sliding Mode-MRAS Strategy

The aim of this paper is to provide a high-performance sensorless control of single phase induction motor drives. The synthesis of second-order sliding mode controllers to drive the rotor speed and the stator currents is based on the adaptive super twisting algorithm. The proposed method for the estimation of speed is based on sliding mode model reference adaptive system (SM-MRAS) observer. Whereas, in order to disturbance and uncertainties cancellation, an adaptive time varying switching gain is designed then adopted. A discrete low pass filter was used to improve the estimator generated signal for practical implementation, representing a very simple design process compared with other chattering reduction methods as adding an observer. The stability of the SM-MRAS speed estimation algorithm is proved using the Lyapunov approach and its robustness is investigated under load conditions. Simulation and experimental results prove the effectiveness of the proposed sensorless speed control algorithm.

Control of Four Switch Three Phase Inverter Fed Induction Motor Drives Based Speed and Stator Resistance Estimation

This paper presents sensorless position and speed control for a four-switch three-phase inverter (FSTPI) fed induction motor drive. Accurate knowledge of stator resistance is of utmost importance for correct operation of a number of speed sensorless induction motor control schemes in the low speed region. Since stator resistance inevitably varies with operating conditions, stable and accurate operation at near-zero speed requires an appropriate identification algorithm for the stator resistance. The paper proposes such an identification algorithm, which is developed for the rotor flux based model reference adaptive system (MRAS) type of the speed estimator in conjunction with a rotor flux oriented control scheme. In this speed estimation method only one (out of the two available) degree of freedom is utilized for speed estimation. It is utilize the second available degree of freedom as a mean for adapting the stator resistance. The parallel stator resistance and rotor speed identification algorithm is developed in a systematic manner, using Popov’s hyper stability theory. It increases the complexity of the overall control system insignificantly and enables correct speed estimation and stable drive operation at near-zero speeds. The proposed speed and position estimator with parallel stator resistance identification for FSTPI fed induction motor at very low speed under high load operation is verified by simulation and experimental results. The results show the robustness of the proposed method with FSTPI. DOI: http://dx.doi.org/10.11591/ijpeds.v4i2.5057

Neural Sensorless Control of Linear Induction Motors by a Full-Order Luenberger Observer Considering the End Effects

This paper proposes a neural based full-order Luenberger adaptive speed observer for sensorless linear induction motor (LIM) drives, where the linear speed is estimated with the total least squares (TLS) EXIN neuron. A novel state space-vector representation of the LIM has been deduced, taking into consideration its dynamic end effects. The state equations of the LIM have been rearranged into a matrix form to be solved, in terms of the LIM linear speed, by any least squares technique. The TLS EXIN neuron has been used to compute online, in recursive form, the machine linear speed. A new gain matrix choice of the Luenberger observer, specifically taking into consideration the LIM dynamic end effects, has been proposed, overcoming the limits of the gain matrix choice based on the rotating-induction-machine model. The proposed TLS full-order Luenberger adaptive speed observer has been tested experimentally on an experimental rig. Results have been compared with those achievable with the TLS EXIN MRAS, the classic MRAS, and the sliding-mode MRAS observers.

A New Sensorless Control Design of Induction Motor Based on Backstepping Sliding Mode Approach

In this paper, we propose a new sensorless control of induction motor (IM). The design of this control is based on backstepping and sliding mode approaches. First, the backstepping control is designed to steer the flux and speed variables to theirs references and to compensate the uncertainties trough appropriate Lyapunov functions. Second, sliding mode controllers (SMC) is used for stator currents control. Finally, we estimate the rotor speed by using the Luenberger observer (LO) and the rotor flux by using the extended Kalman filter (EKF). Simulation results are illustrated and prove the effectiveness of the proposed sensorless control in different working of speed references and against load torque disturbance

Sensorless Stator Field-Oriented Controlled IM Drive at Low Speed withRrEstimator

This paper pertains to a technique of a sensorless indirect stator field-oriented induction motor control, which prevents the accumulative errors incurred by the integrator and the problem relating to the stability of the control system caused by the stator resistance susceptible to temperature variations while conducting the flux estimation directly and computing the synchronous rotary speed. The research adds an adaptive flux observer to estimate the speed of the rotor and uses the fixed trace algorithm (FTA) to execute an online estimation of the slip difference, thereby improving the system of stability under the low rotary speed at regenerating mode and the influence of the rotor resistance on the slip angle. Finally, the paper conducts simulations by Simulink of MATLAB and practices to verify the correctness of the result the paper presents.

Development of Motor Model of Rotor Slot Harmonics for Speed Sensorless Control of Induction Motor

SUMMARYThis paper proposes a novel mathematical dynamic model to represent the steady‐state and transient‐state characteristics of rotor slot harmonics of an induction motor for sensorless control. Although it is well known that the rotor slot harmonics originate from the mechanical structure of the induction motor, a mathematical model that describes the relationship between the stator/rotor currents of the induction motor and the slot harmonics has not yet been proposed. Therefore, in this paper, a three‐phase model of the induction motor that depicts the rotor slot harmonics is developed by taking into consideration the magnetomotive force harmonics and the change in the magnetic air gap caused by the rotor slots. The validity of the proposed model is verified by comparing the experimental results and the calculated values. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(3): 63–74, 2014; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22478

Estimation of Rotor Flux using Neural Network Observer in Speed Sensorless Induction Motor Drive

n speed sensorless controlled induction motor drive, the rotor flux based Model Reference Adaptive System (MRAS) for is more popular. In MRAS, the voltage model equations are used in the reference model, which leads to poor performance of the drive at low speeds. In this paper, a new stator current based MRAS is presented. In this measured stator currents of induction motor are used as a reference model to avoid the use of a pure integrator. Estimated stator currents are used as an adjustable model. The estimation of stator currents requires the information of the rotor flux which can be obtained from the voltage or current model. This encounters instability and dc drift. To overcome these problems, flux observer is proposed based on Neural Network (NN). This offline trained multilayer feed-forward NN flux observer applied to indirect vector controlled speed sensorless induction motor drive has been verified by MATLAB/SIMULINK.

Implementation of sensorless control of induction machines using only fundamental PWM waveforms of a two‐level converter

This study reports the implementation of a sensorless control scheme for AC machines that requires neither a fundamental model observer nor a test-signal. The model is based on saliency detection through the use of fundamental PWM excitation and the measurement of the derivatives of the line currents induced by the PWM voltage vectors. Derivation of the rotor position is possible at low and zero speeds without separate test signals and also at higher speed without the knowledge of the machine's fundamental model. Experimental results showing fully sensorless induction motor control at low and higher speeds validate the principle of this method.

유도 전동기 센서리스 제어를 위한 동기 각속도 오차 보상기를 갖는 향상된 Programmable LPF 자속 추정기

This paper proposes an improved stator flux estimator through ensuring conventional PLPF to act as a pure integrator for sensorless control of induction motors. Conventional PLPF uses the estimated synchronous speed as a cut-off frequency and has the gain and phase compensators. The gain and phase compensators are determined on the assumption that the estimated synchronous angular speed is coincident with the real speed. Therefore, if the synchronous angular speed is not same as the real speed, the gain and phase compensation will not be appropriate. To overcome the problem of conventional PLPF, this paper analyzes the relationship between the synchronous speed error and the phase lag error of the stator flux. Based on the analysis, this paper proposes the synchronous speed error compensation scheme. To achieve a start-up without speed sensor, the current model is used as the stator flux estimator at the standstill. When the motor starts up, the current model should be switched into the voltage model. So a stable transition between the voltage model and the current model is required. This paper proposes the simple transition method which determines the initial values of the voltage model and the current model at the transition moment. The validity of the proposed schemes is proved through the simulation results and the experimental results.

Optimization of Model Reference Adaptive System based Speed Estimation for Speed Sensorless Control of Induction Motors via Differential Evolution Algorithm

Abstract This study proposes an optimally tuned Model Reference Adaptive System (MRAS) based speed estimator using back electromotive force (EMF) vector, which does not require pure integration. The PI (Proportional and Integral) gain coefficients in the speed estimator are optimally determined by utilizing Differential Evolution (DE) algorithm. The performance of the speed estimator is tested with both simulation and real-time experiments for a wide speed range. The obtained results verify the desired performance of speed estimation.