Direct space vector modulation for matrix converter fed dual star induction machine and neuro-fuzzy speed controller

This paper presents the modeling, design, and simulation of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling the speed of the Double Star induction Machine (DSIM), the machine is fed by three phase direct matrix converter which makes directly AC-AC power conversion is modeled using Direct Space Vector Modulation technique(DSVM)  for direct matrix converter. Double star Induction motor is characterized by highly non-linear, complex and time-varying dynamics and inaccessibility of some of the states and outputs for measurements. Hence it can be considered as a challenging engineering problem in the industrial sector. Various advanced control techniques has been devised by various researchers across the world. Some of them are based on the neuro-fuzzy techniques. The main advantage of designing the ANFIS coordination scheme is to control the speed of the DSIM to increase the dynamic performance, to provide good stabilization. To show the effectiveness of our scheme, the proposed method was simulated on an electrical system composed of a 4.5 kW six-phase induction machine and its power inverter. Digital simulation results demonstrate that the deigned ANFIS speed controller realize a good dynamic of the DSIM, a perfect speed tracking with no overshoot, give better performance and high robustness

Total harmonic distortion analysis of inverter fed induction motor drive using neuro fuzzy type-1 and neuro fuzzy type-2 controllers

Introduction. When the working point of the indirect vector control is constant, the conventional speed and current controllers operate effectively. The operating point, however, is always shifting. In a closed-system situation, the inverter measured reference voltages show higher harmonics. As a result, the provided pulse is uneven and contains more harmonics, which enables the inverter to create an output voltage that is higher. Aim. A space vector modulation (SVM) technique is presented in this paper for type-2 neuro fuzzy systems. The inverter’s performance is compared to that of a neuro fuzzy type-1 system, a neuro fuzzy type-2 system, and classical SVM using MATLAB simulation and experimental validation. Methodology. It trains the input-output data pattern using a hybrid-learning algorithm that combines back-propagation and least squares techniques. Input and output data for the proposed technique include information on the rotation angle and change of rotation angle as input and output of produced duty ratios. A neuro fuzzy-controlled induction motor drive’s dynamic and steady-state performance is compared to that of the conventional SVM when using neuro fuzzy type-2 SVM the induction motor, performance metrics for current, torque, and speed are compared to those of neuro fuzzy type-1 and conventional SVM. Practical value. The performance of an induction motor created by simulation results are examined using the experimental validation of a dSPACE DS-1104. For various switching frequencies, the total harmonic distortion of line-line voltage using neuro fuzzy type-2, neuro fuzzy type-1, and conventional based SVMs are provided. The 3 hp induction motor in the lab is taken into consideration in the experimental validations.Вступ. Коли робоча точка непрямого векторного управління стала, традиційні регулятори швидкості та струму працюють ефективно. Проте робоча точка постійно змінюється. У ситуації закритої системи виміряна інвертором опорна напруга показує вищі гармоніки. В результаті імпульс, що подається, нерівномірний і містить більше гармонік, що дозволяє інвертору створювати більш високу вихідну напругу. Мета. У цій статті представлена методика просторової векторної модуляції (SVM) для нейронечітких систем типу 2. Продуктивність інвертора порівнюється з продуктивністю нейронечіткої системи типу 1, нейронечіткої системи типу 2 та класичної SVM з використанням моделювання MATLAB та експериментальної перевірки. Методологія. Навчається шаблон даних введення-виводу, використовуючи алгоритм гібридного навчання, який поєднує у собі методи зворотного поширення помилки та методу найменших квадратів. Вхідні та вихідні дані для запропонованої методики включають інформацію про кут повороту і зміну кута повороту як отримані вхідні і вихідні коефіцієнти заповнення. Динамічні характеристики приводу асинхронного двигуна з нейронечітким управлінням порівнюються з характеристиками звичайного SVM. При використанні нейронечіткого SVM типу 2 асинхронний двигун, показники продуктивності по струму обертаючого моменту і швидкості порівнюються з показниками приводу асинхронного двигуна з нейронечітким управлінням типу 1 та традиційного SVM. Практична цінність. Продуктивність асинхронного двигуна, створеного за результатами моделювання, досліджується з використанням експериментальної перевірки dSPACE DS-1104. Для різних частот перемикання розраховуються загальні гармонічні спотворення лінійної напруги з використанням нейронечіткого управління  типу 2, нейронечіткого управління типу 1 і традиційного SVM. Асинхронний двигун потужністю 3 л.с. у лабораторії враховується під час експериментальних перевірок

BEZPOŚREDNIE STEROWANIE MOMENTEM WIELOFAZOWEGO SILNIKA INDUKCYJNEGO Z ROZMYTYM REGULATOREM PRĘDKOŚCI

The paper presents the Direct Torque Control with Space Vector Modulation (DTC-SVM) of seven-phase induction motor with Fuzzy Logic Speed Controller. The mathematical model of the seven-phase squirrel-cage induction motor and chosen methods of Space Vector Modulation have been presented. Simulation studies of the DTC-SVM with Fuzzy Logic speed controller have been carried out and the results of simulation studies have been presented and discussed. The author original contribution includes analysis and studies of considered control method of seven-phase induction motor.W artykule przedstawiono metodę bezpośredniego sterowania momentem siedmiofazowego silnika indukcyjnego z zastosowaniem metod modulacji wektorowej i rozmytego regulatora prędkości. Przedstawiono model matematyczny siedmiofazowego silnika indukcyjnego klatkowego oraz wybrane metody modulacji wektorowej. Przeprowadzono badania symulacyjne sterowania silnikiem z zastosowaniem metody DTC-SVM i rozmytego regulatora prędkości. Przedstawiono i omówiono wyniki badań symulacyjnych. Oryginalny wkład autora dotyczy analizy i badań przedstawionej metody sterowania silnikiem siedmiofazowym

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis

High-performance motor drives

This article reviews the present state and trends in the development of key parts of controlled induction motor drive systems: converter topologies, modulation methods, as well as control and estimation techniques. Two- and multilevel voltage-source converters, current-source converters, and direct converters are described. The main part of all the produced electric energy is used to feed electric motors, and the conversion of electrical power into mechanical power involves motors ranges from less than 1 W up to several dozen megawatts

Performance Analysis of DTC-SVM Sliding Mode Controllers-Based Parameters Estimator of Electric Motor Speed Drive

This paper is concerned with a framework which unifies direct torque control space vector modulation (DTC-SVM) and variable structure control (VSC). The result is a hybrid VSC-DTC-SVM controller design which eliminates several major limitations of the two individual controls and retains merits of both controllers. It has been shown that obtained control laws are very sensitive to variations of the stator resistance, the rotor resistance, and the mutual inductance. This paper discusses the performances of adaptive controllers of VSC-DTC-SVM monitored induction motor drive in a wide speed range and even in the presence of parameters uncertainties and mismatching disturbances. Better estimations of the stator resistance, the rotor resistance, and the mutual inductance yield improvements of induction motor performances using VSC-DTC-SVM, thereby facilitating torque ripple minimization. Simulation results verified the performances of the proposed approach

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio