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The paper presents the design of a speed and flux observer for the sensorless induction motor (IM) drive. The design is based on the full-order model of the IM in the stationary reference frame. The proposed method consists of an observer with linear feedback that yields the motor fluxes and also estimates the speed using an adaptive law. Convergence conditions are formulated based on Lyapunov's nonlinear stability theory - the design of the feedback gains is done using Sylvester criterion. While this observer structure was discussed in the literature previously, the novelty of the method is given by the Sylvester criterion formulation - this uncovers interesting inequalities and offers insight into the design choices and stability margins of the observer. The method can be used to obtain the field orientation angle and speed needed in a sensorless IM drive. The theory is supported by simulations and experiments.

In this paper, we present a grid-connected wind turbine equipped with double-fed induction generator directly connected to the grid in the stator side and interconnected via a power converter in the rotor side. The aim of this paper is to control the rotor side power converter via a speed sensorless direct torque control using a rotor flux observer based on the sliding mode method combined with the classical Lyapunov stability theory. The speed sensorless direct torque control seeks to provide a tracking of speed and rotor flux in spite of an unpredictable wind fluctuation. To control the grid side converter, a network voltage vector oriented control strategy is developed. The proposed strategies tested under parametric variations and different scenarios of wind speed disturbances, evaluate the system performances.

Much more investigation is done in the low speed operation of IM. High-speed operation is rarely paid attention; since it is assumed that the IM would work successfully in that area. However, the high-speed operation of IM with conventional feedback designing behaves not so well and presents oscillation situation, due to inappropriate placement of eigenvalues of flux observer and deterioration of speed adaptation mechanism. Correspondingly, considering the saturation effect of main flux, this paper proposes a new feedback designing method and improved speed adaptation mechanism.

Vector control system is dependent of parameters of motor, and rotor time constant usually changes with temperature. Through analyzing the influence of rotor time constant variations on the control system performance, a novel identification method based on adaptive flux observer is presented. Different with traditional pole assignment method, it implies robust control theory and Lyapunov stability theory, by solving a linear matrix inequality (LMI) to obtain the feedback gain matrix. The simulation results show that this method can identify the rotor time constant of induction motor accurately, and it has rapid converge, good indiscrimination degree and strong robustness.

The power series approximation method is proposed for real time implementations of a discrete flux observer. The proposed method improves the performance of the discrete flux observer in the case of a low sampling rate and high speed range, where the simple discrete flux observer converted by the Euler method cannot estimate the actual flux precisely. The performance of discrete flux observers with different orders of approximation is compared to find out the proper order of approximation. The validity of the proposed method is verified through simulation and experiment.

In this paper there are outlined the automatic speed adjusting control system performances of a two-phase induction machine (TPIM) with direct field oriented control and using adaptive methods for the estimation of the rotoric flux spatial vector. Starting from the linear model of the two-phase induction machine, there are studied in comparison two solutions used in automatic speed adjusting control: one using the deduction of the spatial vector components of the rotoric flux by indirect field determination and the second using adaptive methods for rotoric flux spatial vector estimation from the two-phase components of the stator voltage and current. Thus there are emphasized the performances of the reduced order Gopinath observer. The operation of the automatic speed adjusting control system, based on solid adaptive estimation of the rotoric flux and indirect determination of the field, was studied using Matlab/SIMULINK real time simulation.

This paper presents a comparative study of field-oriented control (IFOC) and direct-torque control (DTC) of induction motors using an adaptive flux observer. The main characteristics of field-oriented control and direct torque control schemes are studied by simulation, emphasizing their advantages and disadvantages. The performances of the two control schemes are evaluated in terms of torque, current ripples and transient responses to load toque variations. We can nevertheless observe a slight advance of DTC scheme compared to FOC scheme regarding the dynamic flux control performance and the implementation complexity. Consequently, the choice of one or the other scheme will depend mainly on specific requirements of the application.

 Abstract—This paper presents a robust simulation of direct vector control of induction machine (IM) drive on the rotor flux direction with composite model flux observer. In the indirect vector control of IM, current reference values are used for estimation angle of the rotor flux space vector (ARFSV), however using current reference values instead of current real values can decrease accuracy of ARFSV. In the direct vector control, current real values (current feedback) estimate the ARFSV. ARFSV estimation can be performed by current model flux observer and voltage model flux observer. These observers have their own limitations. The composite model reduces disadvantages of every individual ones. Simulation of composite model is applied to induction machines and obtained results compare to the classical current and voltage models. The composite model approach shows great advantages over those classic ones, a.e. speed control over wide range of motor operation and enough short settling time. All these remarkable advantages support application of composite model in ARFSV.

This paper presents an investigation of inverter fault-tolerant operation for a permanent magnet synchronous motor (PMSM) direct torque control (DTC) system under various inverter faults. The performance of a faulty standard 6-switch inverter driven PMSM DTC system is analyzed. To avoid the loss or even disaster caused by the inverter faults, a topology-modified inverter with fault-tolerant capability is introduced, which is reconfigured as a 3-phase 4-switch inverter. The modeling of the 4-switch inverter is then analyzed and a novel DTC strategy with a unique nonlinear perpendicular flux observer and feedback compensation scheme is proposed for obtaining a continuous, disturbance-free drive system. The simulation and experimental results demonstrate that the proposed inverter fault-tolerant PMSM DTC system is able to operate stably and continuously with acceptable static and pretty good dynamic performance.

A flux model, which is capable of both MTPA(Maximum Torque Per Ampere) control and position sensorless control of IPMSMs(Interior Permanent Magnet Synchronous Motors), has been proposed. This paper proposes that the flux is estimated using the full-order observer. And a design method for the full-order observer is also proposed. The design method of the full-order observer that robust flux estimation become possible against the velocity estimation error, by solving γ-positive real problem and H∞ control problem. In this paper, the experimental result of the position sensorless control of IPMSMs shows that a proposed design method of the full-order observer is very useful.

In this paper, a synchronous reluctance motor fed by a matrix converter (MC) is current and flux controlled. Despite the advantages of matrix converters compared to conventional back-to-back converters, the application of these converters for synchronous reluctance motors (SyRMs) is not reported in the literature. The flux linkage on d axis and the current on q axis are closed loop controlled for the sake of a good combination of dynamic response and efficiency. Real-time maximum torque per Ampere usefully minimizes losses at all speeds, in particular at partial load. The input and output vectors of the converter are modulated using indirect space vector modulation technique. A flux observer provides the feedback to the d regulator. The nonlinearities of the converter are identified and compensated, to the benefit of voltage estimation and then flux estimation accuracy. Simulation results show that the presented MC-SyRM drive is promising for compactness and efficiency in critical applications.

This paper presents a model reference adaptive system-based sensorless induction motor drive. In this scheme, an adaptive pseudoreduced-order flux observer is used instead of the adaptive full-order flux observer. The simulation and experimental results show that with the large PI gains for the adaptive scheme, the convergence for the speed estimation is fast, however, higher order harmonics and noises are included in the estimated speed. Usually noises caused by A/D converters and hysteresis current controller. Since the current measurement is noisy, therefore large values of adaptive scheme gains cause the estimated flux and consequently the estimated speed noisy. The desired gains are a trade-off between a high speed of response, and high robustness to noise. Simulation and experimental results show that proposed scheme can estimate the motor speed under various adaptive PI gains and estimated speed can replace to measured speed in sensorless induction motor drives.

This paper presents a continuous approach of sliding-mode current and flux observers for an induction machine. The proposed observer structure both decouples machine equations and makes them completely insensitive to rotor resistance variation. An estimation algorithm based on these observers is proposed to calculate speed and rotor resistance independently. In the proposed algorithm, the speed and rotor resistance are considered to be unknown constants, because the speed and rotor resistance change slowly compared to the electrical variables such as currents and fluxes. The simulation and experimental results demonstrate the good performance of the proposed observer and estimation algorithm and of the overall indirect-field-oriented-controlled system.

A robust and accurate observer for IM speed estimation, not only at normal and high speeds but also at very low and zero speeds, is certainly important and desirable for sensorless IM drives. Many pole placement methods have been proposed to design a good adaptive flux observer that is less sensitive to IM speed; however, most of them have poor dynamic performance at very low and zero speeds. Four different pole placement techniques are discussed in this paper. Three of the four techniques are based on the generalization of existing methods. Authors propose the fourth technique, which is an improvement over the existing schemes. The feedback gain is chosen in such a way that the observer poles are unaffected by motor speed variations. Although all four schemes estimate the motor speed and stator resistance in real time, the proposed technique is superior to others in performance and robustness to motor speed and stator resistance variations and noises.

This paper proposes new identification laws of an adaptive flux observer for speed sensorless vector controls. In speed sensorless vector controls of an induction motor with the adaptive observer, the speed identification system is known to be unstable in a part of regenerating region. In addition, it is pointed out that the stator resistance variation interferes with the speed identification. Thus it is necessary to find an adaptive scheme which can stabilize the identification system.In this paper, firstly, the stability on the parameter identification is discussed from the viewpoint of Popov’s hyper stability. Secondly, identification laws for the speed and the stator resistance are proposed based on the new identification system which is derived by using the augmented error. Finally, effectiveness of the proposed method is shown by experiments.

This paper presents an algorithm for three-phase induction motors rotor flux observation based on a neofuzzy neuron (NFN) network with real-time training featuring quick accurate convergence, great adaptability to system dynamics, good performance over a wide speed range, and low sensitivity to parameter variations (rotor and mutual inductances and rotor resistance) and disturbances. The observer requires only rotor speed and stator current measurements as input signals and. its fuzzy-neural network does not need previous training. Convergence in one step is demonstrated and the influence of the learning rate on performance is analyzed. Both digital simulation and experimental results are presented and show the observer good overall performance.

This paper investigates problems associated with direct torque control (DTC) of PMSM, such as the stator resistance variations, the integration drift and the integration saturation in order to reduce the system ripples. The standard particle filter (PF) algorithm was introduced to DTC system of PMSM. The motor terminal voltages and stator currents are the system input and output variables. and the two stator fluxes are used as system state variables. Then the flux can be estimated according to PF algorithm when the voltages and stator currents have been measured. The method was implemented in Simulink. The simulation results indicate that the system based on PF observer has good performance.

This paper presents a sensorless control technique of a directly driven wind synchronous generator. This approach is based on the adaptive sliding mode flux observer and on the adaptive speed estimator. Two sensorless control strategies are applied to the Permanent Magnet Synchronous Generator (PMSG): in the first step, we have considered the vector (VC) strategy and in the second one, we have applied the sliding mode control (SMC) strategy. Simulation results investigate good performances of both proposed non linear approaches.

In this paper, we present a methodology for the design of a speed sensorless flux observer for induction motors using a behavioral model of the angular speed. We start by developing a reduced order model of the induction motor using complex differential equations. After that, we formulate a behavioral model whose data represents the angular speed of the physical model of the induction motor. This has been done because the original equation governing the rotor speed within the physical model of the machine is highly nonlinear and too complicated to analyse. Furthermore, we use the developed behavioral model in order to design the speed sensorless flux observer for induction motors. The validity of the proposed approach is verified from simulation of the model of the induction motor's flux observer.

This paper presents a novel adaptive flux observer based direct torque and flux control (DTFC) of a permanent magnet synchronous motor (PMSM) drive. An online loss minimization algorithm (LMA) is developed to estimate the air-gap flux so that the motor operates at minimum loss condition while taking the general advantages of the DTFC scheme over the conventional vector control scheme. The proposed DTFC-based PMSM drive incorporating the LMA-based flux observer is implemented in real time using the DSP board DS1104 for a laboratory 5-hp motor. The performance of the proposed LMA-based DTFC control of the PMSM drive is tested in both simulation and experiment at different operating conditions.

This paper investigates a nonlinear adaptive controller (NAC) with sliding mode flux observer (SMFO) for induction motor (IM), which mainly deal with the unknown time-varying nonlinearities and disturbances. In the NAC design, all nonlinearities are assumed unknown, and included in a perturbation term, together with uncertainties and disturbances. The perturbation term is estimated by an extended-state observer (ESO) and the online estimate of the perturbation is used to achieve adaptive linearization. Moreover, a SMFO is employed to estimate the rotor flux. The proposed control method provides a satisfactory speed tracking performance in the presence of parameter variations and load torque disturbance. The performance of the proposed controller is verified by simulation studies and experiments.

The paper discusses the problem of flux estimation for the induction motor (IM) drive and presents a sensorless observer. The intention is to estimate the IM fluxes in the stationary reference frame in order to obtain both the magnitude and the angle of the rotor flux. The flux magnitude is typically used for d axis feedback; the flux angle is needed for field orientation. The paper presents an alternative state-space model of the IM. Based on this, a Lyapunov-type nonlinear state observer with continuous feedback is designed. The paper first assumes that the speed is known and develops a sensored observer; then, this is transformed into a sensorless observer by feeding it with a speed estimate (assumed inaccurate). This method eliminates the speed measurement. The paper shows that, despite the improper speed input, the design yields a partially accurate estimate of the state vector that is sufficient for obtaining the magnitude and angle of the flux. Previous observers developed under the same conditions based on the traditional IM model were only capable of estimating the angle of the flux (but not the magnitude). The novelty is that this method also yields an accurate flux magnitude. It is shown that the equilibrium point of the observer is influenced by the design gains; with high enough gain, the observer converges. The theoretical developments are supported by simulations.

A new vector control system of an induction motor is proposed in this paper to reduce the influence of iron loss, which has been difficult to deal with. Recently, many methods have been proposed to improve the accuracy of torque control, concentrating on the identification of parameters and the adjustment of the controllers. But, it is necessary for experts to tune parameters initially in those methods. The new method can reduce the influence of iron loss by using a robust flux observer. By adding current decoupling control for compensation of the iron loss, a vector control system with high torque linearity can be constructed. © 2001 Scripta Technica, Electr Eng Jpn, 137(3): 59–66, 2001

This paper proposes an approach to determine the gain of closed loop flux observer for an induction machine with respect to robustness and stability criteria. In the companion paper, a sensitivity analysis of flux observer has pointed out the influence of the sampling rate and the parameters mismatch. From this study, an accurate observer can be deduced. The analytical results are checked experimentally, in steady state and during transients. For that aim, an experimental rig has been installed. This paper deals also with a new description of the induction machine drive thanks to Causal Informational Graph. This description is useful for the simulation and for the implementation of the experimental rig.

In the last decades, many vector control techniques have been developed for induction machine to increase their dynamic performances. But they are based on an accurate estimation of flux variables, which are not measurable in conventional induction machines. So, observer strategies are used in induction machine controls. Complex algorithms have been developed, but their long calculation time does not allow a simple implementation in digital form. For this reason, reduced-order observers are often used when a real-time estimation is implemented. If these structures lead to better flux estimations than in the case of an open-loop model, their convergence gains have to be determined and they are sensitive to the parameters value. The authors present a new analytical method to elaborate a reduced-order observer. The influence of the sampling rate is taken into account and the paper investigates the optimal gain, which minimise the sensitivity to the parameters value. In order to measure the observer robustness, the authors define two criteria, which are computed in steady state: the orientation error and the modulus error of the rotor flux. Some examples illustrate the theory and their calculation results are presented.

In recent years, many vector control methods with a flux observer for the induction motors have been developed. In these methods, torque control characteristics deteriorate when an induction motor is driven at low speeds with resistance deviations.In this paper, robust flux observer with optimal feedback gain is proposed in which resistance deviations assume to be system noise, and error equation is derived. Proposed method is shown to be feasible with experimental results.

In the recent years, many speed sensorless control method with adaptive observer of induction motor have been developed. The feedback gain of observer is designed from the responsive viewpoint of the error convergence. When we drive induction motor in the low speed region with each method, the control characteristic is deteriorated. In this paper, we give the design of the speed sensorless adaptive flux observer in the low speed region and propose speed sensorless vector control system with it from the stable viewpoint of the error convergence. And we show experimental results of this method.

This paper proposes a robust-adaptive scheme for position sensorless control of interior permanent magnet synchronous motors (IPMSMs) using ϵ1-modification approach. The feasibility and effectiveness of the proposed method is shown by experimental results in low-speed region. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

An adaptive pseudoreduced-order flux observer for speed sensorless field-oriented control is presented. In comparison with the adaptive full-order flux observer, the proposed method consumes less computational time and illustrates better speed performance. Simulations and experiments on a 3-hp induction motor verify the validity of the proposed method.

There are some papers about the vector controlled induction motor systems with the adaptive secondary flux observer. One observer used in the system with speed sensor has the estimators of the primary resistance and secondary resistance. And another observer used in the system without speed sensor has the estimators of the primary resistance and speed. These systems are stable that the induction motor is driven under power running condition, but are not always stable that it is driven under regenerating condition. So far, the stability under regenerating condition is not made clear.The conventional adaptive secondary flux observer was constituted on dq (fixed) coordinate. In this paper, it is constituted on γδ (rotated) coordinate. The stability of systems on both the coordinates is equivalent. As the state variables of the systems on γδ coordinate are dc, the stability of systems can be investigated around equilibrium points.As the results of investigation, the stability of systems is made clear under the power running condition and the regenerating condition. The systems are stable under the power running condition as known. But the systems are almost never stable under the regenerating condition, in case the observer has the estimators of the primary resistance and secondary resistance, or the observer has the estimators of the primary resistance and speed. Even the regenerating condition, in case the observer has only the estimator of the secondary resistance, or the observer has only the estimator of the speed, the boundaries of stability extend fairly.The appropriateness of investigation results is confirmed by the simulations.

Neste trabalho é apresentado um estudo sobre o controle de velocidade sensorless aplicado ao Motor de Indução Trifásico (MIT) visando sobretudo, melhorar o desempenho da máquina de indução em aplicações na região de baixa frequência de operação. Para tanto, propõe-se uma abordagem utilizando a técnica de controle Direct Torque Control (DTC) com Space Vector Modulation (SVM) em conjunto com o Observador de Fluxo com Modelo de Tensão e Corrente (OFMTC), o que possibilita a estimação precisa da posição do vetor de fluxo do estator em baixa velocidade. Para a estimativa da velocidade do rotor é utilizado a estratégia Model Reference Adaptive System (MRAS) com mecanismo de adaptação fuzzy, a fim de se diminuir a sensibilidade aos parâmetros da máquina. O desempenho da estratégia de controle de velocidade sensorless proposta é testada em simulações com diferentes condições de operação buscando reproduzir alguns dos problemas encontrados em aplicações práticas, utilizando o software Matlab. Os resultados obtidos foram condizentes com resultados encontrados na literatura, comprovando o bom desempenho do sistema de controle de velocidade proposto., This work deals with the sensorless speed control for Three-phase Induction Motor in order to improve its operation at low speed and low frequency. At first, a Direct Torque Control employing Space Vector Pulse with Modulation (SVPWM) based on Flux Observer (voltage and current model) is studied and evaluated due to its high accuracy of estimating the stator-flux at low speed. The Model Adaptive Reference (MRAS) with Fuzzy Controler is chosen in order to estimate the rotor speed. This choice is based on its capability of high performance during Three-phase Induction Motor operation even if the machines parameters and the load change during the operation. At last, some simulations with diferent operational conditions at low speed are carried out in order to test the sensorless control. The results show a good performance and agreed with the results shown in recent papers.

This paper presents an algorithm for enhanced position estimation for permanent-magnet (PM) machine drive working with low resolution Hall-Effect position sensors. The algorithm is based on a modified vector tracking observer structure with modified Hall-Effect sensors' output. The mechanical misalignment problem of the sensors is addresses and a correction mechanism is implemented to compensate for any position estimation errors based on a flux observer. A simulation model is used and experimental setup is built to verify the effectiveness of the proposed control strategy. Finally, Simulation and experimental results are shown to verify the operation of the proposed algorithms.

In this paper a new technique for the adaptive control of the induction motor is proposed. This technique, which is based on nonlinear control and the adaptive flux observer, maintains the performance of the induction motor. Using this observation technique, the output variables and the unknown parameters estimated by the adaptive flux observer, in the nonlinear control of the induction machine made it possible to achieve remarkable performances. To test the robustness of this control technique, variations of the parameters of the induction machine were applied at different times; the simulation results found confirmed our theoretical study and were very satisfactory with respect to the variation of the parameters.

International audience; This paper deals with a novel rotor-flux Kalman observer of a Dual Three-Phase Induction Machine. It will be shown analytically how this observer is built. This rotor-flux estimator can be used for the Direct Rotor Field-Oriented Control. A closed-loop control of this flux is therefore added. Simulation results shows the efficiency of this Kalman filter.

The combination of direct torque control and permanent magnet synchronous motors (PMSMs) provides a highly dynamic drive. In this paper direct torque control method of PMSM is merged with a sensorless control algorithm and a robust flux observer is proposed which results in a high performance highly reliable drive. First a high frequency signal injection method within DTC algorithm is introduced to estimate the rotor position of PMSM. Then the method is modified in order to estimate stator dynamic inductances. The stator inductances are then used in a current model flux observer.

A nonlinear adaptive control algorithm is proposed for induction machines. It is based on a two time-scale observer that allows the on-line identification of three critical uncertain parameters, i.e., load torque and motor stator and rotor resistances. In addition, the set-point of the rotor flux is adjusted in order to minimize the Joule losses and to improve the power efficiency. Experimental results illustrate the feasibility of the developed approach.

This paper focuses on some of the remaining challenges of self-sensing control for permanent magnet synchronous machines (PMSM), which are in detail: combination of EMF-based and magnetic saliency-based methods; influence of the fundamental current control on saliency-based methods; position transducerless system identification of “key parameters/effects” (saturation effects,...); and reduction of computational effort. These demands are taken into account by a novel Model Reference Adaptive System (MRAS) which is based on an armature flux observer.