1,750 research outputs found

    Robust fault tolerant control of induction motor system

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    Research into fault tolerant control (FTC, a set of techniques that are developed to increase plant availability and reduce the risk of safety hazards) for induction motors is motivated by practical concerns including the need for enhanced reliability, improved maintenance operations and reduced cost. Its aim is to prevent that simple faults develop into serious failure. Although, the subject of induction motor control is well known, the main topics in the literature are concerned with scalar and vector control and structural stability. However, induction machines experience various fault scenarios and to meet the above requirements FTC strategies based on existing or more advanced control methods become desirable. Some earlier studies on FTC have addressed particular problems of 3-phase sensor current/voltage FTC, torque FTC, etc. However, the development of these methods lacks a more general understanding of the overall problem of FTC for an induction motor based on a true fault classification of possible fault types.In order to develop a more general approach to FTC for induction motors, i.e. not just designing specific control approaches for individual induction motor fault scenarios, this thesis has carried out a systematic research on induction motor systems considering the various faults that can typically be present, having either “additive” fault or “multiplicative” effects on the system dynamics, according to whether the faults are sensor or actuator (additive fault) types or component or motor faults (multiplicative fault) types.To achieve the required objectives, an active approach to FTC is used, making use of fault estimation (FE, an approach that determine the magnitude of a fault signal online) and fault compensation. This approach of FTC/FE considers an integration of the electrical and mechanical dynamics, initially using adaptive and/or sliding mode observers, Linear Parameter Varying (LPV, in which nonlinear systems are locally decomposed into several linear systems scheduled by varying parameters) and then using back-stepping control combined with observer/estimation methods for handling certain forms of nonlinearity.In conclusion, the thesis proposed an integrated research of induction motor FTC/FE with the consideration of different types of faults and different types of uncertainties, and validated the approaches through simulations and experiments

    Design and Control of Electrical Motor Drives

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    Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

    Disturbance/uncertainty estimation and attenuation techniques in PMSM drives–a survey

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    This paper gives a comprehensive overview on disturbance/uncertainty estimation and attenuation (DUEA) techniques in permanent magnet synchronous motor (PMSM) drives. Various disturbances and uncertainties in PMSM and also other alternating current (AC) motor drives are first reviewed which shows they have different behaviors and appear in different control loops of the system. The existing DUEA and other relevant control methods in handling disturbances and uncertainties widely used in PMSM drives, and their latest developments are then discussed and summarized. It also provides in-depth analysis of the relationship between these advanced control methods in the context of PMSM systems. When dealing with uncertainties,it is shown that DUEA has a different but complementary mechanism to widely used robust control and adaptive control. The similarities and differences in disturbance attenuation of DUEA and other promising methods such as internal model control and output regulation theory have been analyzed in detail. The wide applications of these methods in different AC motor drives (in particular in PMSM drives) are categorized and summarized. Finally the paper ends with the discussion on future directions in this area

    Model predictive MRAS estimator for sensorless induction motor drives

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    Ph. D. ThesisThe project presents a novel model predictive reference adaptive system (MRAS) speed observer for sensorless induction motor drives applications. The proposed observer is based on the finite control set-model predictive control principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS observers. Extensive simulation and experimental tests have been carried out to evaluate the performance of the proposed observer. Both the simulation and the experimental results show improved performance of the MRAS scheme in both open and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller. However, some of the experimental results show oscillations in the estimated rotor speed, especially at light loading conditions. Furthermore, due to the use of the voltage equation in the reference model, the scheme remains sensitive, to a certain extent, to the variations in the machine parameters. Therefore, to reduce rotor speed oscillations at light loading conditions, an adaptive filter is employed in the speed extraction mechanism, where an adaptation mechanism is proposed to adapt the filter time constant depending on the dynamic state of the system. Furthermore, a voltage compensating method is employed in the reference model of the MP-MRAS observer to address the problems associated with sensitivity to motor parameter variation. The performance of the proposed scheme is evaluated both experimentally and by simulation. Results confirm the effectiveness of the proposed scheme for sensorless speed control of IM drives

    Nonlinear continuous-time generalised predictive control

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    The development of the nonlinear version of the Continuous-time Generalised Predictive Control (NCGPC) is presented. Unlike the linear version, the nonlinear version is developed in state-space form and shown to include Nonlinear Generalised Minimum Variance (NGMV), and a new algorithm, Nonlinear Predictive Generalised Minimum Variance (NPGMV), as special cases. Through simulations, it is demonstrated that NCGPC can deal with nonlinear systems whose relative degree is not well defined and nonlinear systems with unstable zero dynamics. Geometric approaches, such as exact linearisation, are shown to be included in the NCGPC as special cases

    High-Gain Observer–Based Sliding Mode Control of Multimotor Drive Systems

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    Multimotor drive systems have been widely used in many modern industries. It is a nonlinear, multi-input, multi-output (MIMO) and strong-coupling complicated system, including the effect of friction, elastic, and backlash. The control law for this drive system much depends on the determining of the tension. However, it is hard to obtain this tension in practice by using a load cell or a pressure meter due to the accuracy of sensors or external disturbance. In order to solve this problem, a high-gain observer is proposed to estimate the state variables in this drive system, such as speeds and tension. An emerging proposed technique in the control law is the use of high-gain observers together with adaptive sliding mode control scheme to obtain a separation principle for the stabilization of whole system. The theory analysis and simulation results point out the good effectiveness of the proposed output feedback for the drive system

    Nonlinear Model Predictive Control for Induction Motor Drive

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    Induction Motors

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    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
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