384 research outputs found

    Speed -Sensorless Estimation And Position Control Of Induction Motors For Motion Control Applications

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    Thesis (Ph.D.) University of Alaska Fairbanks, 2006High performance sensorless position control of induction motors (IMs) calls for estimation and control schemes which offer solutions to parameter uncertainties as well as to difficulties involved with accurate flux and velocity estimation at very low and zero speed. In this thesis, novel control and estimation methods have been developed to address these challenges. The proposed estimation algorithms are designed to minimize estimation error in both transient and steady-state over a wide velocity range, including very low and persistent zero speed operation. To this aim, initially single Extended Kalman Filter (EKF) algorithms are designed to estimate the flux, load torque, and velocity, as well as the rotor, Rr' or stator, Rs resistances. The temperature and frequency related variations of these parameters are well-known challenges in the estimation and control of IMs, and are subject to ongoing research. To further improve estimation and control performance in this thesis, a novel EKF approach is also developed which can achieve the simultaneous estimation of R r' and Rs for the first time in the sensorless IM control literature. The so-called Switching and Braided EKF algorithms are tested through experiments conducted under challenging parameter variations over a wide speed range, including under persistent operation at zero speed. Finally, in this thesis, a sensorless position control method is also designed using a new sliding mode controller (SMC) with reduced chattering. The results obtained with the proposed control and estimation schemes appear to be very compatible and many times superior to existing literature results for sensorless control of IMs in the very low and zero speed range. The developed estimation and control schemes could also be used with a variety of the sensorless speed and position control applications, which are challenged by a high number of parameter uncertainties

    Observer-based Fault Detection and Diagnosis for Mechanical Transmission Systems with Sensorless Variable Speed Drives

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    Observer based approaches are commonly embedded in sensorless variable speed drives for the purpose of speed control. It estimates system variables to produce errors or residual signals in conjunction with corresponding measurements. The residual signals then are relied to tune control parameters to maintain operational performance even if there are considerable disturbances such as noises and component faults. Obviously, this control strategy outcomes robust control performances. However, it may produce adverse consequences to the system when faults progress to high severity. To prevent the occurrences of such consequences, this research proposes the utilisation of residual signals as detection features to raise alerts for incipient faults. Based on a gear transmission system with a sensorless variable speed drive (VSD), observers for speed, flux and torque are developed for examining their residuals under two mechanical faults: tooth breakage with different degrees of severities and shortage of lubricant at different levels are investigated. It shows that power residual signals can be based on to indicate different faults, showing that the observer based approaches are effective for monitoring VSD based mechanical systems. Moreover, it also shows that these two types fault can be separated based on the dynamic components in the voltage signals

    Machine Model Based Speed Estimation Schemes for Speed Encoderless Induction Motor Drives: a Survey

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    Speed Estimation without speed sensors is a complex phenomenon and is overly dependent on the machine parameters. It is all the more significant during low speed or near zero speed operation. There are several approaches to speed estimation of an induction motor. Eventually, they can be classified into two types, namely, estimation based on the machine model and estimation based on magnetic saliency and air gap space harmonics. This paper, through a brief literature survey, attempts to give an overview of the fundamentals and the current trends in various machine model based speed estimation techniques which have occupied and continue to occupy a great amount of research space

    Machine model based Speed Estimation Schemes for Speed Encoderless Induction Motor Drives: A Survey

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    Speed Estimation without speed sensors is a complex phenomenon and is overly dependent on the machine parameters. It is all the more significant during low speed or near zero speed operation. There are several approaches to speed estimation of an induction motor. Eventually, they can be classified into two types, namely, estimation based on the machine model and estimation based on magnetic saliency and air gap space harmonics. This paper, through a brief literature survey, attempts to give an overview of the fundamentals and the current trends in various machine model based speed estimation techniques which have occupied and continue to occupy a great amount of research space

    Industrial applications of the Kalman filter:a review

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    Model reference adaptive backstepping control of double star induction machine with extended Kalman sensorless control

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    Introduction. Newly, the design of a controller for speed control of double star induction motor as a research focus. Consequently, backstepping technique is used to recursively construct a stable control law for speed and flux. Nevertheless, this control law coming from backstepping requires the knowledge of speed and flux values; in practice the measurement sensors are expensive and fragile. The novelty of this work consists to propose a control strategy which based on accurate Kalman filter observer that estimates speed, flux and torque. This extended Kalman filter is an optimal state estimator and is usually applied to a dynamic system that involves a random noise environment. Purpose. Apply a backstepping control of double star induction motor based on principle of rotor flux orientation. This approach consists in finding a Lyapunov function that allows deducing a control law and a modified adaptation rule is referred and sufficient conditions for the stability of the command-observer, in contrast to other techniques who use nonlinear principle. Results. The simulation results are shown to illustrate the performance of the proposed scheme under parametric uncertainties by simulation on MATLAB. The obtained results showed the robustness of the sensorless control in front of load and parameters variation of double stator induction motor. The research directions of the model were determined for the subsequent implementation of results with simulation samples.Вступ. Новітня розробка контролера для регулювання швидкості асинхронного двигуна з подвійною зіркою є предметом дослідження. Отже, метод відступу використовується для рекурсивної побудови стабільного закону керування швидкістю та потоком. Тим не менш, цей закон керування, що випливає з відступу, вимагає знання значення швидкості та потоку; на практиці вимірювальні датчики коштовні та недовговічні. Новизна даної роботи полягає в тому, щоб запропонувати стратегію управління на основі точного спостерігача за фільтром Калмана, який оцінює швидкість, потік і крутний момент. Цей розширений фільтр Калмана є оптимальним засобом оцінки стану і зазвичай застосовується до динамічної системи, яка включає середовище випадкових шумів. Мета. Застосування підходу відступу до керування асинхронним двигуном з подвійною зіркою на основі принципу орієнтації потоку ротора. Цей підхід полягає у знаходженні функції Ляпунова, яка дозволяє вивести закон керування та модифіковане правило адаптації, а також достатні умови для стабільності спостерігача команд, на відміну від інших методик, які використовують нелінійний принцип. Результати. Результати моделювання наведені для ілюстрації роботи запропонованої схеми за параметричних невизначеностей шляхом моделювання на MATLAB. Отримані результати показали надійність безсенсорного керування перед зміною навантаження та параметрів асинхронного двигуна з подвійним статором. Визначені напрямки дослідження моделі для подальшої реалізації результатів на прикладах моделювання

    Particle swarm optimization-based stator resistance observer for speed sensorless induction motor drive

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    This paper presents a different technique for the online stator resistance estimation using a particle swarm optimization (PSO) based algorithm for rotor flux oriented control schemes of induction motor drives without a rotor speed sensor. First, a conventional proportional-integral controller-based stator resistance estimation technique is used for a speed sensorless control scheme with two different model reference adaptive system (MRAS) concepts. Finally, a novel method for the stator resistance estimation based on the PSO algorithm is presented for the two MRAS-type observers. Simulation results in the Matlab/Simulink environment show good adaptability of the proposed estimation model while the stator resistance is varied to 200% of the nominal value. The results also confirm more accurate stator resistance and rotor speed estimation in comparison with the conventional technique

    New Model Reference Adaptive System Speed Observer for Field-Oriented Control Induction Motor Drives Using Neural Networks

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    One of the primary advantages of field-oriented controlled induction motor for high performance application is the capability for easy field weakening and the full utilization of voltage and current rating of the inverter to obtain a wide dynamic speed rangeThis paper describes a Model Reference Adaptive System (MRAS) based scheme using Artificial Neural Network (ANN) for online speed estimation of sensorless vector controlled induction motor drive. The proposed MRAS speed observer uses the current model as an adaptive model. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator. The simulation results show good performance in various operating conditions. Also Performance analysis of speed estimator with the change in resistances of stator is presented. Simulation results show this estimator robust to parameter variations especially resistances of stator

    High performance speed control of single-phase induction motors using switching forward and backward EKF strategy

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    The aim of this research is to provide a high performance vector control of single-phase Induction Motor (IM) drives. It is shown that in the rotating reference frame, the single-phase IM equations can be separated into forward and backward equations with the balanced structure. Based on this, a method for vector control of the single-phase IM, using two modified Rotor Field- Oriented Control (RFOC) algorithms is presented. In order to accommodate forward and backward rotor fluxes in the presented controller, an Extended Kalman Filter (EKF) with two different forward and backward currents that are switched interchangeably (switching forward and backward EKF), is proposed. Simulation results illustrate the effectiveness of the proposed algorithm
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