Fuzzy Direct Torque-controlled Induction Motor Drives for Traction with Neural Compensation of Stator Resistance

In this chapter, a new method for stator resistance compensation in direct torque control (DTC) drives, based on neural networks, is presented. The estimation of electromagnetic torque and stator flux linkages using the measured stator voltages and currents is crucial to the success of DTC drives. The estimation is dependent only on one machine parameter, which is the stator resistance. Changes of the stator resistances cause errors in the estimated magnitude and position of the flux linkage and therefore in the estimated electromagnetic torque. Parameter compensation by means of stator current phasor error has been proposed in literature. The proposed approach in this chapter is based on a principle that states the error between the measured current magnitude of the stator feedback and the stator’s command, verified with neural network, is proportional to the variation of the stator resistance and is mainly caused by the motor temperature and the varying stator frequency. Then the correction value of stator resistance is achieved by means of a fuzzy controller. For the first time, a combination of neural control and fuzzy control approach in stator resistance variations based on the stator current is presented. The presented approach efficiently estimates the correct value of stator resistance

DTC based on SVM for induction motor sensorless drive with fuzzy sliding mode speed controller

By using the direct torque control (DTC), robust response in ac drives can be produced. Ripples of currents, torque and flux are oberved in steady state. space vector modulation (SVM) applied in DTC and used for a sensorless induction motor (IM) with fuzzy sliding mode speed controller (FSMSC) is studied in this paper. This control can minimize the torque, flux, current and speed pulsations in steady state. To estimate the rotor speed and stator flux the model reference adaptive system (MRAS) is used that is designed from identified voltages and currents. The FSMSC is used to enhance the efficiency and the robustness of the presented system. The DTC transient advantage are maintained, while better quality steady-state performance is produced in sensorless implementation for a wide speed range. The drive system performances have been checked by using Matlab Simultaion, and successful results have been obtained. It is deduced that the proposed control system produces better results than the classical DTC

A simple method to reduce torque ripple and mechanical vibration in direct torque controlled permanent magnet synchronous motor

The Direct Torque Control (DTC) technique of Permanent Magnet Synchronous Motor (PMSM) receives increasing attention due to its simplicity and robust dynamic response compared with other control techniques. The classical switching table based DTC presents large flux, torque ripples and more mechanical vibrations in the motor. Several studies have been reported in the literature on classical DTC. However, only limited studies that actually discuss or evaluate the classical DTC. This paper proposes a simple DTC method / Switching table for PMSM, to reduce flux and torque ripples as well as mechanical vibrations. In this paper two DTC schemes are proposed. The six sector and twelve sector methodology is considered in DTC scheme I and DTC scheme II, respectively. In both DTC schemes a simple modification is made in the classical DTC structure that is by eliminating two level inverter available in the classical DTC is replaced by three level Neutral Point Clamped (NPC) inverter. To further improve the performance of the proposed DTC scheme I, the available 27 voltage vectors are allowed to form different groups of voltage vectors such as Large - Zero (LZ), Medium - Zero (MZ) and Small - Zero (SZ), where as in DTC scheme II, all the voltage vectors are considered to form a switching table. Based on these groups, new switching table is proposed. The proposed DTC schemes are comparatively investigated with the classical DTC and existing literatures from the aspects of theory analysis and computer simulations. It can be observed that the proposed techniques can significantly reduce the flux, torque ripples, mechanical vibrations and improves the quality of current waveform compared with traditional and existing methods

A simple method to reduce torque ripple in direct torque-controlled permanent-magnet synchronous motor by using vectors with variable amplitude and angle

In this paper, a modified direct torque control (DTC) for permanent-magnet synchronous machines, which enables important torque- and flux-ripple reduction by using voltage vectors with variable amplitude and angle, is proposed. In the proposed DTC, the amplitudes of torque and flux errors are differentiated and employed to regulate the amplitude and angle of the output voltage vectors online, which are finally synthesized by space-vector modulation (SVM). Two simple formulas are developed to derive the amplitude and angle of the commanding voltage vectors from the errors of torque and flux only. The conventional switching table and hysteresis controllers are eliminated, and a fixed switching frequency is obtained with the help of SVM. Stator flux is estimated from an improved voltage model, which is based on a low-pass filter with compensations of the amplitude and phase. The proposed DTC is comparatively investigated with the existing SVM-DTC from the aspects of theory analysis, computer simulation, and experimental validation. The simulation and experimental results prove that the proposed DTC is very simple and provides excellent steady-state response, quick dynamic performance, and strong robustness against external disturbance and control-parameter variations. © 2006 IEEE

Intelligent control for torque ripple minimization in combined vector and direct controls for high performance of IM drive

Abstract -In Conventional Combined Vector and Direct Controls (VC-DTC) of induction motor, stator current is very rich in harmonic components. It leads to high torque ripple of induction motor in high and low speed region. To solve this problem, a control method based on the concept of fuzzy logic approach is used. The control scheme proposed uses stator current error as variable. Through the fuzzy logic controller rules, the choice of voltage space vector is optimized and then torque and speed are controlled successfully with a less ripple level in torque response, which improve the system's performance. Simulation results trough MATLAB/SIMULINK® software gave results that justify the claims

Minimization of torque ripples in direct torque control of induction motor at low speeds

Direct Torque Control (DTC) of induction motor has attracted a considerable attention in the motor drives industry. The key merits of DTC include fast torque dynamic response, simple structure, insensitivity to motor’s parameters. Nevertheless, DTC inherently suffers from two major downsides namely: high torque ripples and variable switching frequency. This thesis presents a new technique to minimize the torque ripples inherited in the digital-based DTC of induction motor. The typical discrete-based DTC imposes a delay time which frequently allows the torque to overshoot beyond hysteresis bands. This triggers the selection of reverse voltage vectors which, in turn, cause large torque decrements. The torque ripples become of great significance at low speeds where torque overshoot is most likely to occur due to steep positive torque slope. A multi-level DC link voltage is proposed to vary the DC voltage of Voltage Source Inverter (VSI) according to motor’s speed. By varying the DC link voltage, the torque slopes can be controlled and, hence, the torque overshoots are mostly avoided. Therefore, the torque ripples are significantly minimized. The viability of proposed technique has been validated using MATLAB/Simulink software. Results show the proposed technique may yield over 50% reduction in the RMS torque ripples while maintaining a low switching frequency. Also, the torque dynamic response is maintained as good as in the conventional DTC schem

Modified Direct Torque Control of Induction Motor Drives

Over past years, direct torque control (DTC) has proven to be a powerful technique for controlling induction motors since, its simple structure, fast performance, and robustness. However, conventional DTC has a major problem in selecting the optimum voltage vector in order to provide fast torque response, due to the nature of the hysteresis controller. This thesis presents a new control topology for DTC, which enables fast torque response and reduced steady state ripple. The proposed scheme utilizes an optimized inverter voltage vector selection process ensuring a higher rate of torque increment during transient periods. Further, two nonlinear adaptation mechanisms are used to replace the hysteresis controllers thus obtain enhanced torque and stator flux regulation. One scheme is based on sliding mode theory and the other method is based on fuzzy logic strategy. A comprehensive simulation study has been performed to evaluate the performances of the proposed sector-advancing algorithm under the two nonlinear control methodologies. The corresponding simulation results and discussion are presented for each section. It is concluded that the proposed DTC algorithms with sliding mode and fuzzy logic strategies demonstrate better characteristics in both transient and steady state operation with regards to the conventional DTC.Electrical Engineerin

Online loss minimization based direct torque and flux control of IPMSM drive

With the advent of high energy rare earth magnetic material such as, third generation neodymium-iron-boron (NdFeB), permanent magnet synchronous motor (PMSM) is becoming more and more popular in high power industrial applications (e.g., high-speed railway) due to its advantageous features such as high energy density, stable parameters, high power factor, low noise and high efficiency as compared to the conventional ac motors. Over the years, vector control and direct torque and flux control (DTFC) techniques have been used for high performance motor drives. But, the DTFC is faster than that of conventional vector control as the DTFC scheme doesn't need any coordinate transformation, pulse width modulation (PWM) and current regulators. The DTFC utilizes hysteresis band comparators for both flux and torque controls. Most of the past researches on DTFC based motor drives mainly concentrated on the development of the inverter control algorithm with less torque ripple as it is the major drawback of DTFC. The torque reference value is obtained online based on motor speed error between actual and reference values through a speed controller. Traditionally, researchers chose a constant value of air-gap flux reference based on trial and error method which may not be acceptable for high performance drives as the air-gap flux changes with operating conditions and system disturbance. Efficient high performance drives require fast and accurate speed response to cope with disturbances and algorithm to minimize motor losses. However, if the reference air-gap flux is maintained constant it is not possible to control the motor losses. Therefore, this thesis presents a novel loss minimization based DTFC scheme for interior type PMSM drive so that the drive system can maintain both high efficiency and high dynamic performance. An online model based 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 DTFC over conventional vector control. The performance the proposed LMA based DTFC for PMSM drive is tested in both simulation and real-time implementation at different operating conditions. The results verify the effectiveness of the proposed flux observer based DTFC scheme for PMSM drive

Commande directe du couple appliquée à une machine à reluctance commutée à trois phases

Le moteur à reluctance commutée (SRM) est connu pour sa conception simple, sans aimants permanents, bobinage au rotor et son bas cout de production et une bonne robustesse qui lui confère conception, même sous la perte d’une phase ou de plus et d’opérer dans un environnement industriel très contraignant. Néanmoins ce moteur présente de nombreux inconvénients due à sa double saillance polaire, ses caractéristiques magnétiques et un couple de sortie hautement non linéaires très instable et qui présente de fortes perturbations. La double saillance du moteur ne permettant pas d’exciter ce dernier par une alimentation CA conventionnelle et de commander ce moteur utilisant la théorie des champs tournants. En outre, en raison des caractéristiques de sortie de couple non linéaires du moteur, une ondulation à couple élevé est inhérente au moteur, sauf si une stratégie de réduction de l’ondulation de couple est utilisée. Afin de parer à la non linéarité du couple de sortie et de diminuer les fortes perturbations de couple, plusieurs techniques ont été utilisées. La technique de contrôle du couple direct (DTC) est une excellente technique qui a donné de bons résultats pour ce type de moteur, et pour ce faire notre travail peut être considérée comme une contribution à l’amélioration de la DTC. Nous considérons spécifiquement le remplacement des régulateurs à hystérésis par ceux utilisant les techniques d’intelligence artificielle (logique floue, réseaux de neurones et neuro-flou), avec une concentration plus prononcée pour la technique de régulation par logique floue avec une structure Takagi-Sugeno comme le cœur de notre travail. Pour finir, nous avons utilisé la commande adaptative pour varier les paramètres du régulateur flou en temps réel lors de perturbations paramétriques du SRM et notamment pour parer à la variation de la résistance statorique. La loi de contrôle et la loi adaptative développées, garantissent que tous les signaux dans le système en boucle fermée sont limités en amplitude, alors que la conception du contrôleur est basée sur la synthèse de Lyapunov.Switched Reluctance (RS) Motors have an intrinsic simplicity and low cost that makethem well suited to many applications. Furthermore, the motors have a high robustness due to the ability to operate with the loss of one or more motor phases and are thus well suited to operate in harsh industrial environments. However, the motor has many drawbacks due to the motor’s doubly salient structure as well as highly non-linear torque output and magnetization characteristics. The double salient structure leads to the inability to excite the motor using conventional ac motor rotating field theory to the motor. Furthermore, due to the motor’s non-linear torque output characteristics, a hightorque ripple is inherent in the motor unless a torque ripple reduction strategy is employed. to overcome the non-linearity of the output torque and reduce torque ripple,several techniques have been developed. Direct torque control (DTC) is an excellent technique which has had good results for this type of motor. our work, is a contribution to the improvement of the DTC by the substitution of the hysteresis regulators by thoseusing artificial intelligence techniques (fuzzy logic, neural networks and neuro-fuzzy), with a more pronounced concentration in our study for fuzzy logic regulation technique with Takagi-Sugeno structure. Finally, we used the adaptive control to vary the fuzzy regulator parameters in real time during parametric disturbance of the SRM and especially during stator resistance variation. The control law and the adaptive law developed guarantee the delimitation of all the signals in the closed-loop system and the controller design is made according to Lyapunov's synthesi