2,489 research outputs found

    Stability analysis of the extended Kalman filter for Permanent Magnet Synchronous Motor

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    This paper presents a sensorless direct field oriented control fed interior permanent magnet synchronous motor (IPMSM) by using a known mathematical tool. The Kalman filter is an observer for linear and non-linear systems and is based on the stochastic intromission, in others words, noise. It is a question of studying the state and measurement noise covariance matrices Q and R on the stability of the Extended Kalman Filter. This last is used for the d, q stator current, mechanical speed, rotor position, stator resistance and the load torque estimation. The simulation tests carried out on Matlab Simulink showed that the matrix R improves much more quality of the estimated states while the matrix Q allows the improvement of the estimation process convergence

    Dynamic Performance Analysis of a Five-Phase PMSM Drive Using Model Reference Adaptive System and Enhanced Sliding Mode Observer

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    This paper aims to evaluate the dynamic performance of a five-phase PMSM drive using two different observers: sliding mode (SMO) and model reference adaptive system (MRAS). The design of the vector control for the drive is firstly introduced in details to visualize the proper selection of speed and current controllers’ gains, then the construction of the two observers are presented. The stability check for the two observers are also presented and analyzed, and finally the evaluation results are presented to visualize the features of each sensorless technique and identify the advantages and shortages as well. The obtained results reveal that the de-signed SMO exhibits better performance and enhanced robustness compared with the MRAS under different operating conditions. This fact is approved through the obtained results considering a mismatch in the values of stator resistance and stator inductance as well. Large deviation in the values of estimated speed and rotor position are observed under MRAS, and this is also accompanied with high speed and torque oscillations

    Sensorless flux-weakening control of permanent-magnet brushless machines using third harmonic back EMF

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    The sensorless control of brushless machines by detecting the third harmonic back electromotive force is a relatively simple and potentially low-cost technique. However, its application has been reported only for brushless dc motors operating under normal commutation. In this paper, the utility of the method for the sensorless control of both brushless dc and ac motors, including operation in the flux-weakening mode, is demonstrated

    Industrial applications of the Kalman filter:a review

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    Stator Resistance Estimation Using Adaptive Estimation via a Bank of Kalman Filters

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    Accurate and efficient control of electric motors is dependent on knowledge of motor parameters such as the resistance and the inductance of the winding. However, these parameters are often unavailable to the control designer because they are dependent on the motor design and may change due to environmental effects such as temperature. An accurate real-time method to determine the values of these unknown parameters can improve motor performance over the entire operating range. In this work, a parameter estimation technique based on a bank of Kalman filters is used to adaptively estimate the motor winding resistance. Simulation results for a 3.5 horsepower interior permanent magnet (IPM) synchronous motor operating at rated torque demonstrate that this technique may be used for real-time estimation of motor parameters

    Estimation of rotor flux of an induction machine

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    The objective of this dissertation is to estimate rotor flux of an IM. Some of the material is focused on the functional block of the IM i.e. Torque estimator, Speed estimator etc. while a subsequent part deals with estimation of rotor flux. The dissertation is organized as follows:Chapter 1 describes background information of the machines then it focuses on the methodology how on to approach the task on a particular time with the help of Gantt chart.Chapter 2 presents the basic principals of rotating magnetic field of the IM and asserts brief overview of the AC machines. Later it talks about different kinds of IM rotors suggesting which one is good. It is crucial to start with good and appropriate reviews which were verified by numerous journals. Literature review is presented by analysing the previous work. (Busawan et al., 2001) summarises that a nonlinear observers for the estimation of the rotor flux and the load torque in an induction motor. The observers are designed on the basis of the standard alpha - beta Park's model. Finally, fuzzy logic is mentioned in more detailed way and Membership functions were also discussedChapter 3 explains the dynamic model of induction machine plant and the model was presented. Then the model is analysed, developed in MATLAB-SIMULINK which was discussed in Chapter 4. By considering following assumptions, dynamic model is implemented i.e. it should be symmetrical two-pole, three phase windings. Slotting effects are neglected, Permeability of the iron part is infinite, and iron losses are neglected. Dynamic d-q model and Axes transformation is implemented on stationary reference frame (a-b-c). Lastly torque equation is derived.Chapter 4 is the heart of this project by scrutinizing the model thoroughly and by introducing fuzzy controller logic using MATLAB-SIMULINK; simulations are performed to estimate the functional block such as torque, speed, flux, resistance with and without fuzzy logic. Results were obtained for different blocks and the m-file, DTC, Flux table were obtained and presented in the Appendixes.Chapter 5 concludes the simulation results and concentrates mainly on the future direction what more can be done to improve the platform in a more efficient manner

    Comparative Study of Sensorless Control Methods of PMSM Drives

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    Recently, permanent magnet synchronous motors (PMSMs) are increasingly used in high performance variable speed drives of many industrial applications. This is because the PMSM has many features, like high efficiency, compactness, high torque to inertia ratio, rapid dynamic response, simple modeling and control, and maintenance-free operation. In most applications, the presence of such a position sensor presents several disadvantages, such as reduced reliability, susceptibility to noise, additional cost and weight and increased complexity of the drive system. For these reasons, the development of alternative indirect methods for speed and position control becomes an important research topic. Many advantages of sensorless control such as reduced hardware complexity, low cost, reduced size, cable elimination, increased noise immunity, increased reliability and decreased maintenance. The key problem in sensorless vector control of ac drives is the accurate dynamic estimation of the stator flux vector over a wide speed range using only terminal variables (currents and voltages). The difficulty comprises state estimation at very low speeds where the fundamental excitation is low and the observer performance tends to be poor. The reasons are the observer sensitivity to model parameter variations, unmodeled nonlinearities and disturbances, limited accuracy of acquisition signals, drifts, and dc offsets. Poor speed estimation at low speed is attributed to data acquisition errors, voltage distortion due the PWM inverter and stator resistance drop which degrading the performance of sensorless drive. Moreover, the noises of system and measurements are considered other main problems. This paper presents a comprehensive study of the different methods of speed and position estimations for sensorless PMSM drives. A deep insight of the advantages and disadvantages of each method is investigated. Furthermore, the difficulties faced sensorless PMSM drives at low speeds as well as the reasons are highly demonstrated. Keywords: permanent magnet, synchronous motor, sensorless control, speed estimation, position estimation, parameter adaptation

    Permanent magnet synchronous motor sensorless control based on rotor flux observer with low-pass filter adaptation

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    This paper presents a strategy for a permanent magnet synchronous motor sensorless vector control based on rotor flux estimation considering a rotor saliency. The integration problem in the stator flux estimation was solved by replacing the integrator with a low-pass filter. The low-pass filter parametric adaptation algorithm with phase delay compensation, based on Bode diagrams was designed for the rotor angular position estimation accuracy improving. The proposed adaption algorithm allowed to expand a stable motor control with a high accuracy in the rotor position estimation down to 15 rpm. Also the developed rotor angular position estimation algorithm together with adaptive field weakening algorithm provides a sable motor operation with a high accuracy in the rotor position estimation at the high speed

    Differential-Algebraic Approach to Speed and Parameter Estimation of the Induction Motor

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    This thesis considers a differential-algebraic approach to estimating the speed and rotor time constant of an induction motor using only the measured terminal voltages and currents. It is shown that the induction motor speed satisfies both a second-order and a third-order polynomial equation whose coefficients depend the stator voltages, stator currents, and their derivatives. Further, it is shown that as long as the stator electrical frequency is nonzero, the speed is uniquely determined by these polynomials. The speed so determined is then used to stabilize a dynamic (Luenberger type) observer to obtain a smoothed speed estimate. With full knowledge of the machine parameters and filtering of the sensor noise, simulations and experiments indicate that this estimator has the potential to provide low speed (including zero speed) control of an induction motor under full load. A differential-algebraic approach is also used to obtain an estimate of the rotor time constant of an induction motor, again using only the measured stator voltages and currents. Experimental results are presented to demonstrate the practical use of the identification method
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