Optimized Adaptive Sliding-mode Position Control System for Linear Induction Motor Drive

[[abstract]]This paper proposes an optimized adaptive position control system applied for a linear induction motor (LIM) drive taking into account the longitudinal end effects and uncertainties including the friction force. The dynamic mathematical model of an indirect field-oriented LIM drive is firstly derived for controlling the LIM. On the basis of a backstepping control law, a sliding mode controller (SMC) with embedded fuzzy boundary layer is designed to compensate the lumped uncertainties during the tracking control of periodic reference trajectories. Since it is difficult to obtain the bound of lumped uncertainties in advance in practical applications, an adaptive tuner based on the sense of Lyapunov stability theorem is derived to adjust the fuzzy boundary parameters in real-time. It is a quite complicated process of parameter tuning, especially for the proposed controller, due to the difficulty arisen from lacking of the accurate mathematical model of a system accompanied with unknown disturbance. Therefore, the soft-computing technique is adopted for off-line optimizing the controller parameters. The effectiveness of the proposed control scheme is validated through simulations and experiments for several scenarios. Finally, the advantages of performance improvement and robustness are illustrated at the end of the optimization procedure.[[conferencetype]]國際[[conferencedate]]20130410~20130412[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Paris, Franc

Genetic algorithm optimized robust nonlinear observer for a wind turbine system based on permanent magnet synchronous generator

© 2022 ISA. Published by Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.isatra.2022.02.004This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.Peer reviewe

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines

Field Oriented Sliding Mode Control of Surface-Mounted Permanent Magnet AC Motors: Theory and Applications to Electrified Vehicles

Permanent magnet ac motors have been extensively utilized for adjustable-speed traction motor drives, due to their inherent advantages including higher power density, superior efficiency and reliability, more precise and rapid torque control, larger power factor, longer bearing, and insulation life-time. Without any proportional-and-integral (PI) controllers, this paper introduces novel first- and higher-order field-oriented sliding mode control schemes. Compared with the traditional PI-based vector control techniques, it is shown that the proposed field oriented sliding mode control methods improve the dynamic torque and speed response, and enhance the robustness to parameter variations, modeling uncertainties, and external load perturbations. While both first- and higher-order controllers display excellent performance, computer simulations show that the higher-order field-oriented sliding mode scheme offers better performance by reducing the chattering phenomenon, which is presented in the first-order scheme. The higher-order field-oriented sliding mode controller, based on the hierarchical use of supertwisting algorithm, is then implemented with a Texas Instruments TMS320F28335 DSP hardware platform to prototype the surface-mounted permanent magnet ac motor drive. Last, computer simulation studies demonstrate that the proposed field-oriented sliding mode control approach is able to effectively meet the speed and torque requirements of a heavy-duty electrified vehicle during the EPA urban driving schedule

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

Robust fault tolerant control of induction motor system

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

Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

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

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

Industrial applications of the Kalman filter:a review

International audienc