Journal articles on the topic 'Rotor current estimation and control'
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1
Chen, Jenn Yih. "Passivity-Based Parameter Estimation and Position Control of Induction Motors via Composite Adaptation." Applied Mechanics and Materials 284-287 (January 2013): 1894–98. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1894.
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This paper proposes the parameters estimation and position control of an induction motor drive by using the composite adaptation scheme. First, in the rotor reference frame, the input-output linearization theory was employed to decouple the mechanical rotor position and the rotor flux amplitude at the transient state. An open-loop current model rotor flux observer was utilized for estimating the flux, and then the adaptive laws for estimating the rotor resistance, moment of inertia, viscous friction coefficient, and load torque. The passive properties of the flux observer, rotor resistance estimator, and composite adaptive position controller were analyzed based on the passivity theorem. According to the properties, the overall position control system was proved to be globally stable without using Lyapunov-type arguments. Experimental results are finally provided to show that the proposed method is robust to variations of the motor mechanical parameters, rotor resistance, and load torque disturbances. Moreover, good position tracking response and characteristics on parameter estimation can be achieved.
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Zhang, Tao, Wei Ni, Hui Ping Zhang, and Sha Sha Wu. "Sensorless Control of IPMSM Using Modified Current Slope Estimation Method." Applied Mechanics and Materials 150 (January 2012): 100–104. http://dx.doi.org/10.4028/www.scientific.net/amm.150.100.
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When the permanent magnet synchronous motor is operated at a low speed. The rotor position and speed are very difficult to estimate using the extended flux or back EMF method. A novel modified current slope estimating method is used to estimate the rotor position and speed in low speed in this paper. The mathematical models of an interior permanent magnet synchronous motor (IPMSM) are deduced. The basic principle of modified current slope method is introduced. The simulation control system is built based on Matlab and a TMS320LF2407 digital signal processor is used to execute the rotor position and speed estimation. The experimental and simulation results have shown that the rotor position and speed can be accurately estimated in a low-speed operating region.
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Chen, Jenn Yih, and Bean Yin Lee. "Adaptive Parameter Estimation and Position Control of Induction Motors Based on Passivity Theorem." Materials Science Forum 626-627 (August 2009): 489–94. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.489.
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This paper presents the passivity-based rotor resistance and mechanical paramters estimation, and the position control for induction motors. Firstly, the input-output linearization theory is employed to decouple the rotor flux amplitude and the rotor position at the transient state. An open-loop current model flux observer then estimates the rotor flux. Furthermore, we adopted the gradient algorithm to design adaptive laws to estimate the rotor resistance, moment of inertia, viscous coefficient, and load torque. The passive properties of the feedback connection of the rotor flux observer to the rotor resistance estimator, and the position controller are analyzed by the passivity theorem. According to the properties, the overall control system is proved to be globally stable without using Lyapunov-type arguments. Finally, experimental results are provided to show that the proposed method is robust to variations of the mechanical parameters and load torque disturbances. Moreover, good position tracking response and parameters estimating characteristic can be obtained.
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Li, Shun, and Xinxiu Zhou. "Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems." Energies 11, no. 10 (September 25, 2018): 2554. http://dx.doi.org/10.3390/en11102554.
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A large number of permanent magnet synchronous motors (PMSMs) are used to drive coal conveyer belts in coal enterprises. Sensorless energy conservation control has important economic value for these enterprises. The key problem of sensorless energy conservation control for PMSMs is how to decompose the stator current through estimating the rotor position and speed accurately. Then a double closed loop control for stator current and speed is formed to make the stator current drive the motor as an entire torque current. In this paper, the proposed startup estimation algorithm can utilize the current model of PMSM as reference model to estimate the rotor speed and position in the startup stages. It is not dependent on the back electromotive force (EMF) which is used by the general estimation algorithm. However, the resistance will change with the temperature shift of stator windings, and these changes will cause the reference current model to be inaccurate and influence the rotor speed and position estimation precision. Thus, startup estimation algorithm switches to the proposed operation estimation algorithm which is based on the robust sliding mode theory and is not dependent on the motor parameters. The advantages of startup estimation algorithm and operation estimation algorithm are combined to form a hybrid observer. This hybrid observer realizes the accurate estimation of the rotor speed and position from start-up to operation. The stator current is precisely decomposed. The excitation current is controlled to 0. Meanwhile, the double closed-loop control of current and speed is achieved. The stator current is as entire torque current to drive motor. The closed-loop control, which is based on the proposed rotor position and speed estimation algorithm, achieve the most efficient conversion of electrical energy.
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Zerdali, Emrah, and Murat Barut. "Extended Kalman Filter Based Speed-Sensorless Load Torque and Inertia Estimations with Observability Analysis for Induction Motors." Power Electronics and Drives 3, no. 1 (December 1, 2018): 115–27. http://dx.doi.org/10.2478/pead-2018-0002.
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Abstract This paper aims to introduce a novel extended Kalman filter (EKF) based estimator including observability analysis to the literature associated with the high performance speed-sensorless control of induction motors (IMs). The proposed estimator simultaneously performs the estimations of stator stationary axis components of stator currents and rotor fluxes, rotor mechanical speed, load torque including the viscous friction term, and reciprocal of total inertia by using measured stator phase currents and voltages. The inertia estimation is done since it varies with the load coupled to the shaft and affects the performance of speed estimation especially when the rotor speed changes. In this context, the estimations of all mechanical state and parameters besides flux estimation required for high performance control methods are performed together. The performance of the proposed estimator is tested by simulation and real-time experiments under challenging variations in load torque and velocity references; and in both transient and steady states, the quite satisfactory estimation performance is achieved.
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Wang, Zhanshan, Longhu Quan, and Xiuchong Liu. "Sensorless SPMSM Position Estimation Using Position Estimation Error Suppression Control and EKF in Wide Speed Range." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/480640.
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The control of a high performance alternative current (AC) motor drive under sensorless operation needs the accurate estimation of rotor position. In this paper, one method of accurately estimating rotor position by using both motor complex number model based position estimation and position estimation error suppression proportion integral (PI) controller is proposed for the sensorless control of the surface permanent magnet synchronous motor (SPMSM). In order to guarantee the accuracy of rotor position estimation in the flux-weakening region, one scheme of identifying the permanent magnet flux of SPMSM by extended Kalman filter (EKF) is also proposed, which formed the effective combination method to realize the sensorless control of SPMSM with high accuracy. The simulation results demonstrated the validity and feasibility of the proposed position/speed estimation system.
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Donga, Kan, Li Jun Diaob, Da Nan Sun, Bai Shui Ruan, and Zhi Gang Liu. "MRAS-Based Rotor Time Constant Estimation for Indirect Vector Controlled Induction Motor Drive." Advanced Materials Research 433-440 (January 2012): 6812–18. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.6812.
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Decoupling the stator current into magnetizing current and torque current, the vector control technique improves the performance of AC drive system effectively. However, the rotor time constant varies widely with rotor temperature and the flux level of the machine, which decreases the quality of the drive system. By the contrastive analysis of the variable current on-line estimation methods, this paper uses the Model Reference Adaptive System (MRAS) and designs a set of self-adaption estimation arithmetic which has its basis on the Lyapunov theorem of stability. The simulation shows that the estimation arithmetic has the characteristics of fast convergence speed, few stability errors, good track performance and etc. On the basis of simulation of the rotor time constant on-line estimation, this paper designs the system of vector control with the rotor time constant on-line estimation and has the simulation. According to the simulation results, applying the estimation to the vector control system can improve the performance of the system effectively and establish the theoretical basis of the research on the high-performance AC drive system.
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Bobrov, Maxim, Vladislav Artamonov, and Nikita Dubov. "Flux linkage estimation strategies for sensorless field-oriented control of doubly-fed induction motor drive." E3S Web of Conferences 244 (2021): 09014. http://dx.doi.org/10.1051/e3sconf/202124409014.
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In this paper authours propose two different strategies of flux linkage estimation for sensorless FOC system of doubly-fed induction motor drive implementation. Possibility to measure currents and voltages of rotor and stator circuits in doubly-fed motor gives place to a simplier flux linkage observers model. Functional scheme of electric drive and two models of flux linkage observers are proposed - a model using the voltage and a model using the rotor current. The stability of the present field-oriented control system when implementing these flux-linkage estimations strategies are investigated using LabView software. The results of theoretical research are confirmed by simulation results in Matlab software.
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Abedinzadeh, Taher, and Sajjad Tohidi. "A comprehensive sensorless control of DFIG-based wind turbines." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 35, no. 1 (January 4, 2016): 27–43. http://dx.doi.org/10.1108/compel-09-2014-0236.
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Purpose – The purpose of this paper is to present an improved approach for estimation of the rotor position and speed of doubly fed induction generator, which can be used in vector control and direct torque control (DTC) schemes. Design/methodology/approach – Some novel equations are developed for calculation of the rotor position and rotor speed. Such equations do not need to the value of stator flux linkage and just, measured values of the stator voltage and currents as well as rotor current are required to be known. Findings – The simulation results verify the satisfactory steady-state and dynamic performance of proposed approach with both the vector control and DTC schemes. The results show that the proposed estimation approach benefits from the starting on the fly, robustness against the variations of the most of the stator and rotor parameters and immunity against the noise. Originality/value – The proposed estimation approach is novel and the outcome of the research of authors. It is simple and effective and, no approximation is made in the calculations. The simulation results demonstrate that the proposed scheme can be successfully implemented in various control strategies, e.g. DTC and vector control.
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Hussien, Mohamed G., Wei Xu, Yi Liu, and Said M. Allam. "Rotor Speed Observer with Extended Current Estimator for Sensorless Control of Induction Motor Drive Systems." Energies 12, no. 19 (September 21, 2019): 3613. http://dx.doi.org/10.3390/en12193613.
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The aim of paper is to investigate an efficient sensorless control method with vector-control technique for the induction motor (IM) drive systems. The proposed technique relies on the indirect rotor-field orientation control scheme (IRFOC). All sensorless control techniques are greatly affected by the observation of the speed estimation procedure. So, an efficacy new algorithm for estimating the rotor speed of the adopted machine is proposed. In addition, a simple effective method to estimate the machine rotor currents is suggested. The adopted rotor-speed observer is based on the concept of IRFOC method and the phase-axis relationships of IM. To ensure the capability of the proposed sensorless speed-control system, a simulation model is developed in the MATLAB/Simulink software environment. The robustness of the new control method is analyzed under parameter uncertainty issue. Furthermore, comprehensive experimental results are obtained. The whole obtained results confirm the validity of the proposed observer for sensorless speed control capability. The given results also verify the effectiveness of the suggested sensorless control system-based IRFOC for speed-control drive systems of IM. Moreover, the results assure that the presented rotor-speed observer is effectively robust via any parameter changes.
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Karanayil, Baburaj, Muhammed Fazlur Rahman, and Colin Grantham. "Identification of Induction Motor Parameters in Industrial Drives with Artificial Neural Networks." Advances in Fuzzy Systems 2009 (2009): 1–10. http://dx.doi.org/10.1155/2009/241809.
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This paper presents a new method of online estimation of the stator and rotor resistance of the induction motor in the indirect vector-controlled drive, with artificial neural networks. The back propagation algorithm is used for training of the neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, is investigated with the help of simulations for variations in the stator and rotor resistance from their nominal values. Both types of resistance are estimated experimentally, using the proposed neural network in a vector-controlled induction motor drive. Data on tracking performances of these estimators are presented. With this approach, the rotor resistance estimation was found to be insensitive to the stator resistance variations both in simulation and experiment.
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Luo, Yung-Chang, Zhi-Sheng Ke, and Ying-Piao Kuo. "Sensorless Rotor-Field Oriented Controlled Induction Motor Drive with Particle Swarm Optimization Algorithm Speed Controller Design Strategy." Mathematical Problems in Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/861462.
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A sensorless rotor-field oriented control induction motor drive with particle swarm optimization algorithm speed controller design strategy is presented. First, the rotor-field oriented control scheme of induction motor is established. Then, the current-and-voltage serial-model rotor-flux estimator is developed to identify synchronous speed for coordinate transformation. Third, the rotor-shaft speed on-line estimation is established applying the model reference adaptive system method based on estimated rotor-flux. Fourth, the speed controller of sensorless induction motor drive is designed using particle swarm optimization algorithm. Simulation and experimental results confirm the effectiveness of the proposed approach.
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Brando, Gianluca, Adolfo Dannier, and Ivan Spina. "Performance Analysis of a Full Order Sensorless Control Adaptive Observer for Doubly-Fed Induction Generator in Grid Connected Operation." Energies 14, no. 5 (February 25, 2021): 1254. http://dx.doi.org/10.3390/en14051254.
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This paper focuses on the performance analysis of a sensorless control for a Doubly Fed Induction Generator (DFIG) in grid-connected operation for turbine-based wind generation systems. With reference to a conventional stator flux based Field Oriented Control (FOC), a full-order adaptive observer is implemented and a criterion to calculate the observer gain matrix is provided. The observer provides the estimated stator flux and an estimation of the rotor position is also obtained through the measurements of stator and rotor phase currents. Due to parameter inaccuracy, the rotor position estimation is affected by an error. As a novelty of the discussed approach, the rotor position estimation error is considered as an additional machine parameter, and an error tracking procedure is envisioned in order to track the DFIG rotor position with better accuracy. In particular, an adaptive law based on the Lyapunov theory is implemented for the tracking of the rotor position estimation error, and a current injection strategy is developed in order to ensure the necessary tracking sensitivity around zero rotor voltages. The roughly evaluated rotor position can be corrected by means of the tracked rotor position estimation error, so that the corrected rotor position is sent to the FOC for the necessary rotating coordinate transformation. An extensive experimental analysis is carried out on an 11 kW, 4 poles, 400 V/50 Hz induction machine testifying the quality of the sensorless control.
14
Li, Haohao, Qigong Chen, Wei Xie, and Shouzhong Lei. "Research On Sensorless Control Of Permanent Magnet Synchronous Motor." Journal of Physics: Conference Series 2174, no. 1 (January 1, 2022): 012073. http://dx.doi.org/10.1088/1742-6596/2174/1/012073.
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Abstract Aiming at the problem that there is no position sensor to observe the rotor position and speed of the built-in permanent magnet synchronous motor under the traditional method of high frequency rotating voltage signal injection, the estimation accuracy of rotor position and speed is low because of the use of a variety of filters in the signal demodulation process. The generalized second-order integrator is used to replace the traditional filters to extract the high frequency response current. In order to reduce the filtering delay problem existing in the traditional signal demodulation method, a new signal demodulation method is proposed, and the rotor position estimation is compensated with appropriate phase compensation. At the same time, appropriate phase compensation is carried out for the estimation of rotor position By constructing IPMSM sensorless vector control simulation module in Simulink simulation, compared with the traditional high-frequency injection method, the improved algorithm can estimate the rotor magnetic pole position more accurately and faster in the process of sensorless control of the motor in the low speed range, and has better stability introduction.
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Luo, Yung-Chang, and Wei-An Huang. "Sensorless rotor field direct orientation controlled induction motor drive with particle swarm optimization algorithm flux observer." Journal of Low Frequency Noise, Vibration and Active Control 38, no. 2 (January 17, 2019): 692–705. http://dx.doi.org/10.1177/1461348418824942.
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A speed estimation scheme based on the particle swarm optimization algorithm flux observer is proposed for a sensorless rotor field direct orientation controlled induction motor drive. The stator current and rotor flux was used to establish both the rotor field direct orientation controlled induction motor drive and the rotor-flux observer. The estimated synchronous angle position was acquired from a current-and-voltage parallel-model rotor estimator for implementation of the exact coordinate transformation to achieve a perfect rotor field direct orientation controlled induction motor drive. The rotor-flux observer was designed using the Lyapunov stability theory, and the estimated rotor speed was derived from the developed the rotor-flux estimator; this estimated speed was unaffected by the slip speed. The gain matrix of this flux observer was obtained using the particle swarm optimization algorithm because it is simple, achieves rapid convergence, and is suitable for a variety of conditions. This system was simulated using the MATLAB/Simulink® toolbox, and all the control algorithms were realized by a TI DSP 6713-and-F2812 control card. Both simulation and experimental results confirmed the effectiveness of the proposed approach.
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Park, Gwangmin, Gyeongil Kim, and Bon-Gwan Gu. "Sensorless PMSM Drive Inductance Estimation Based on a Data-Driven Approach." Electronics 10, no. 7 (March 26, 2021): 791. http://dx.doi.org/10.3390/electronics10070791.
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In the permanent magnet synchronous motor (PMSM) sensorless drive method, motor inductance is a decisive parameter for rotor position estimation. Due to core magnetic saturation, the motor current easily invokes inductance variation and degrades rotor position estimation accuracy. For a constant load torque, saturated inductance and inductance error in the sensorless drive method are constant. Inductance error results in constant rotor position estimation error and minor degradations, such as less optimal torque current, but no speed estimation error. For a periodic load torque, the inductance parameter error periodically fluctuates and, as a result, the position estimation error and speed error also periodically fluctuate. Periodic speed error makes speed regulation and load torque compensation especially difficult. This paper presents an inductance parameter estimator based on polynomial neural network (PNN) machine learning for PMSM sensorless drive with a period load torque compensator. By applying an inductance estimator, we also proposed a magnetic saturation compensation method to minimize periodic speed fluctuation. Simulation and experiments were conducted to validate the proposed method by confirming improved position and speed estimation accuracy and reduced system vibration against periodic load torque.
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Lin, Faa-Jeng, Syuan-Yi Chen, Wei-Ting Lin, and Chih-Wei Liu. "An Online Parameter Estimation Using Current Injection with Intelligent Current-Loop Control for IPMSM Drives." Energies 14, no. 23 (December 4, 2021): 8138. http://dx.doi.org/10.3390/en14238138.
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An online parameter estimation methodology using the d-axis current injection, which can estimate the distorted voltage of the current-controlled voltage source inverter (CCVSI), the varying dq-axis inductances, and the rotor flux, is proposed in this study for interior permanent magnet synchronous motor (IPMSM) drives in the constant torque region. First, a d-axis current injection-based parameter estimation methodology considering the nonlinearity of a CCVSI is proposed. Then, during current injection, a simple linear model is developed to model the cross- and self-saturation of the dq-axis inductances. Since the d-axis unsaturated inductance is difficult to obtain by merely using the recursive least square (RLS) method, a novel tuning method for the d-axis unsaturated inductance is proposed by using the theory of the maximum torque per ampere (MTPA) with the combination of the RLS method. Moreover, to improve the bandwidth of the current loop, an intelligent proportional-integral-derivative (PID) neural network controller with improved online learning algorithm is adopted to replace the traditional PI controller. The estimated the dq-axis inductances and the rotor flux are adopted in the decoupled control of the current loops. Finally, the experimental results at various operating conditions of the IPMSM in the constant torque region are given.
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Hou, Wenbao, Guojun Tan, and Zang Ling. "Low-Speed Sensorless Control for the Interior Permanent Magnet Synchronous Motors with Sliding Discrete Fourier Transform." Mathematical Problems in Engineering 2021 (October 16, 2021): 1–10. http://dx.doi.org/10.1155/2021/9922418.
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An efficient estimation of the rotor position has always been a premise of the reliable operation for the interior permanent magnet synchronous motors (IPMSM), especially for low-speed conditions because of the small back electromotive force (EMF) and low signal-to-noise ratio (SNR). The commonly used observation method, e.g., sliding mode observer (SMO), is suitable for these surface mounted motors and has no great adaptability to the saliency. In this paper, a novel rotor position (including the real-time position and initial position) estimation method was proposed based on the traditional high-frequency signal injection method. Firstly, high-frequency signals were injected to induce the high-frequency current components which contain the rotor position information. Then, the sliding discrete Fourier transform (SDFT) algorithm was used to extract the amplitudes of the induced current components which could be used to get the real-time and initial rotor positions by a proportional integral (PI) regulator and a polarity identification. Lastly, with the established experiments’ platform, the estimation tests of the rotor position at a low speed have been completed to make verification of the effectiveness of the approach studied in this paper.
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Kali, Yassine, Maarouf Saad, Jesus Doval-Gandoy, and Jorge Rodas. "Discrete Terminal Super-Twisting Current Control of a Six-Phase Induction Motor." Energies 14, no. 5 (March 1, 2021): 1339. http://dx.doi.org/10.3390/en14051339.
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In this manuscript, the high-accuracy stator currents tracking issue is considered for a six-phase induction motor subject to external perturbations and uncertainties due to unmeasurable rotor currents and electrical parameter variations. To achieve the control goals, the common two-cascade controllers structure is required for this type of motor. The first controller in the outer loop consists of a proportional integral to regulate the speed. Then, the second is the proposed inner nonlinear stator currents controller based on a robust discrete-time terminal super-twisting algorithm supported by the time-delay estimation method. For the design procedure, the discrete-time stator currents dynamics are derived; for example, the vector of the matched perturbations and unmeasurable rotor currents are specified to simplify the estimation. A detailed stability analysis of the closed-loop error dynamics using Lyapunov theory is given. Finally, a real asymmetrical six-phase induction motor is used to implement in real-time the developed method and to illustrate its effectiveness and robustness. The results obtained reveal a satisfactory stator currents tracking in steady state and transient conditions and under variation in the magnetizing inductance. Moreover, a comparative study with an existing method in steady state for two different rotor speeds is presented to show the superiority of the proposed discrete-time technique.
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Utrata, Grzegorz, Jaroslaw Rolek, and Andrzej Kaplon. "The Novel Rotor Flux Estimation Scheme Based on the Induction Motor Mathematical Model Including Rotor Deep-Bar Effect." Energies 12, no. 14 (July 12, 2019): 2676. http://dx.doi.org/10.3390/en12142676.
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During torque transients, rotor electromagnetic parameters of an induction motor (IM) vary due to the rotor deep-bar effect. The accurate representation of rotor electromagnetic parameter variability by an adopted IM mathematical model is crucial for a precise estimation of the rotor flux space vector. An imprecise estimation of the rotor flux phase angle leads to incorrect decoupling of electromagnetic torque control and rotor flux amplitude regulation which in turn, causes deterioration in field-oriented control of IM drives. Variability of rotor electromagnetic parameters resulting from the rotor deep-bar effect can be modeled by the IM mathematical model with rotor multi-loop representation. This paper presents a study leading to define the unique rotor flux space vector on the basis of the IM mathematical model with rotor two-terminal network representation. The novel rotor flux estimation scheme was validated with the laboratory test bench employing the IM of type Sg 132S-4 with two variants of rotor construction: a squirrel-cage rotor and a solid rotor manufactured from magnetic material S235JR. The accuracy verification of the rotor flux estimation was performed in a slip frequency range corresponding to the IM load adjustment range up to 1.30 of the stator rated current. This study proved the correct operation of the developed rotor flux estimation scheme and its robustness against electromagnetic parameter variability resulting from the rotor deep-bar effect in the considered slip frequency range.
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Égető, Tamás, and Balázs Farkas. "Model Reference Adaptive System for the Online Rotor Resistance Estimation in the Slip-Ring Machine Based Test-bench." Periodica Polytechnica Electrical Engineering and Computer Science 62, no. 4 (June 26, 2018): 149–54. http://dx.doi.org/10.3311/ppee.12495.
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Motor control algorithms with high dynamics are generally based on two basic approach field oriented control (FOC) and direct torque control (DTC). The idea of the first one is to decompose the stator current based on the rotor flux, the second one controls the torque based on the stator flux. Therefore, the FOC is very sensitive to the parameter accuracy regarding the drive performance. That is why it is crucial to verify the parameter identification in the real environment. On the other hand, the parameter sensitivity of DTC is much smaller since the stator flux estimation requires only the knowledge of the stator resistance. The article focuses on the verification of rotor resistance identification in the FOC based drive system by means of the slip ring machine based test bench. The recommended procedure calculates the torque based on the stator current and flux to implement model reference adaptive system for online rotor resistance estimation without signal injection.
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Wang, Shuang, Jianfei Zhao, and Kang Yang. "High Frequency Square-Wave Voltage Injection Scheme-Based Position Sensorless Control of IPMSM in the Low- and Zero- Speed Range." Energies 12, no. 24 (December 14, 2019): 4776. http://dx.doi.org/10.3390/en12244776.
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In this paper, a new sensorless control scheme with the injection of a high-frequency square-wave voltage of an interior permanent-magnet synchronous motor (IPMSM) at low- and zero-speed operation is proposed. Conventional schemes may face the problems of obvious current sampling noise and slow identification in the process of magnetic polarity detection at zero speed operation, and the effects of inverter voltage error on the rotor position estimation accuracy at low speed operation. Based on the principle analysis of d-axis magnetic circuit characteristics, a method for determining the direction of magnetic polarity of d-axis two-opposite DC voltage offset by uninterruptible square-wave injection is proposed, which is fast in convergence rate of magnetic polarity detection and more distinct. In addition, the strategy injects a two-opposite high-frequency square-wave voltage vectors other than the one voltage vector into the estimated synchronous reference frame (SRF), which can reduce the effects of inverter voltage error on the rotor position estimation accuracy. With this approach, low-pass filter (LPF) and band-pass filter (BPF), which are used to obtain the fundamental current component and high-frequency current response with rotor position information respectively in the conventional sensorless control, are removed to simplify the signal process for estimating the rotor position and further improve control bandwidth. Finally, the experimental results on an IPMSM drive platform indicate that the rotor position with good steady state and dynamic performance can be obtained accurately at low-and zero-speed operation with the sensorless control strategy.
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Adamczyk, Michal, and Teresa Orlowska-Kowalska. "Virtual Current Sensor in the Fault-Tolerant Field-Oriented Control Structure of an Induction Motor Drive." Sensors 19, no. 22 (November 15, 2019): 4979. http://dx.doi.org/10.3390/s19224979.
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Designing electrical drives resistant to the failures of chosen sensors has recently become increasingly popular due to the possibility of their use in fault-tolerant control (FTC) systems including drives for electric vehicles. In this article, a virtual current sensor (VCS) based on an algorithmic method for the reconstruction of the induction motor (IM) phase currents after current sensor faults was proposed. This stator current estimator is based only on the measurements of the DC-bus voltage in the intermediate circuit of the voltage-source inverter (VSI) and a rotor speed. This proposal is dedicated to fault-tolerant vector controlled IM drives, where it is necessary to switch to scalar control as a result of damage to the current sensors. The proposed VCS allows further uninterrupted operation of the direct rotor-field oriented control (DRFOC) of the induction motor drive. The stator current estimator has been presented in the form of equations, enabling its practical implementation in a microprocessor system. Simulation studies of the proposed algorithm in an open and closed-loop DRFOC structure are presented under different operation conditions of the drive system. The experimental verification of the proposed method is also presented and the accuracy of the stator current estimation algorithm is analyzed under various operating conditions of the drive system.
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Qi, Xin, Chang Song Wang, and Xiang Hua Ma. "Sensorless Vector Control of Induction Motor Based on Machine Model." Advanced Materials Research 572 (October 2012): 371–75. http://dx.doi.org/10.4028/www.scientific.net/amr.572.371.
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Spatial orientation and magnitude of the rotor flux is essential for vector control of induction motor. Traditionally, current model serves for rotor flux estimation and rotor must be measured by speed sensor. Due to advantages of low cost and high reliability, control the induction motor without sensor draws great attention of scholars around the world. Closed-loop observers or open-loop estimators are used for such purpose. In this paper a new method of sensorless vector control of induction motor is proposed and simulation is implemented to verify the scheme.
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Mahsahirun, Siti Nursyuhada, Nik Rumzi Nik Idris, Zulkifli Md Yusof, and Tole Sutikno. "Non-parametric induction motor rotor flux estimator based on feed-forward neural network." International Journal of Power Electronics and Drive Systems (IJPEDS) 13, no. 2 (June 1, 2022): 1229. http://dx.doi.org/10.11591/ijpeds.v13.i2.pp1229-1237.
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The conventional induction motor rotor flux observer based on current model and voltage model are sensitive to parameter uncertainties. In this paper, a non-parametric induction motor rotor flux estimator based on feed-forward neural network is proposed. This estimator is operating without motor parameters and therefore it is independent from parameter uncertainties. The model is trained using Levenberg-Marquardt algorithm offline. All the data collection, training and testing process are fully performed in MATLAB/Simulink environment. A forced iteration of 1,000-epochs is imposed in the training process. There are overall 603,968 datasets are used in this modeling process. This four-input two-output neural network model is capable of providing rotor flux estimation for field-oriented control systems with 3.41e-9 mse and elapsed 28 minutes 49 seconds training time consumption. This proposed model is tested with reference speed step response and parameters uncertainties. The result indicates that the proposed estimator improves voltage model and current model rotor flux observers for parameters uncertainties.
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Wang, Qing Long, and Shu Ying Yang. "Sensorless Control of Doubly-Fed Induction Generator Based on Adaptive Sliding-Mode Observer." Advanced Materials Research 860-863 (December 2013): 337–41. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.337.
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In this paper, a rotor flux based variable-structure model reference adaptive system (MRAS) observers is proposed for speed observer in a sensorless controlled doubly fed induction generator (DFIG) aligned with the stator flux. In the strategy, two rotor flux models with different structure are used. The rotor flux voltage model without including rotor position item is used as reference model, and the rotor flux current model including rotor position item as adjustable model. A slide-mode surface is formulated from the errors between the two models, and the rotor speed estimation can be obtained by a sliding mode algorithm. Meanwhile the one order inertial link is used to avoid suffering from integrator drift effects in voltage model. Simulation results confirm the validity of the approach.
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Wei, Wen Xiang, and Xiao Ping Zhang. "Flux and Speed Estimation Based on the Extended State Observer for Speed Sensorless Control of Indirect Field Oriented Induction Motor Drives." Applied Mechanics and Materials 273 (January 2013): 414–18. http://dx.doi.org/10.4028/www.scientific.net/amm.273.414.
Full textAbstract:
A flux observer based on the extended state observer (ESO) is proposed for rotor flux estimation and speed identification of indirect field oriented induction motor drives system. The uncertain component including rotor resistance and speed in the stator current equation is extended to a new state, the ESO is then constructed. By the current estimate error, the uncertain component convergences to its actual value and the accurate rotor flux, speed and the rotor time constant are obtained. The accuracy of the ESO independent the rotor resistance and load torque variations, simulations under high and low speed show that the proposed method achieves prefect robust, and the validity and practicability is verified by simulation results.
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Wang, Yuanlin, Xiaocan Wang, Wei Xie, and Manfeng Dou. "Full-Speed Range Encoderless Control for Salient-Pole PMSM with a Novel Full-Order SMO." Energies 11, no. 9 (September 13, 2018): 2423. http://dx.doi.org/10.3390/en11092423.
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For salient-pole permanent magnet synchronous motor (PMSM), the amplitude of extended back electromotive force (EEMF) is determined by rotor speed, stator current and its derivative value. Theoretically, even at extremely low speed, the back EEMF can be detected if the current in q-axis is changing. However, it is difficult to detect the EEMF precisely due to the current at low speed. In this paper, novel full-order multi-input and multi-output discrete-time sliding mode observer (SMO) is built to detect the rotor position. With the proposed rotor position estimation technique, the motor can start up from standstill and reverse between positive and negative directions without a position sensor. The proposed method was evaluated by experiment.
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Qiu, Chunyuan, and Baojiang Sun. "Position Sensorless Control of Switched Reluctance Motor under Magnetic Field Saturation." E3S Web of Conferences 256 (2021): 01040. http://dx.doi.org/10.1051/e3sconf/202125601040.
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When the switched reluctance motor is running, as the motor phase current increases, the magnetic circuit of the motor will gradually saturate, which affects the estimation of the special position of the motor rotor. Aiming at the above problems, this paper proposes a positionless control method for switched reluctance motors under the condition of magnetic field saturation. Firstly, the Fourier phase inductance function of switched reluctance motor is established, and then the component of Fourier phase inductance function affected by magnetic field saturation is eliminated mathematically. Research the method of estimating the position and angle of the rotor based on the inductance positioning point. This paper takes a 12\8 motor as an example to verify the effectiveness of the method by simulation.
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Tanvir, Aman A., and Adel Merabet. "Artificial Neural Network and Kalman Filter for Estimation and Control in Standalone Induction Generator Wind Energy DC Microgrid." Energies 13, no. 7 (April 5, 2020): 1743. http://dx.doi.org/10.3390/en13071743.
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This paper presents an improved estimation strategy for the rotor flux, the rotor speed and the frequency required in the control scheme of a standalone wind energy conversion system based on self-excited three-phase squirrel-cage induction generator with battery storage. At the generator side control, the rotor flux is estimated using an adaptive Kalman filter, and the rotor speed is estimated based on an artificial neural network. This estimation technique enhances the robustness against parametric variations and uncertainties due to the adaptation mechanisms. A vector control scheme is used at the load side converter for controlling the load voltage with respect to amplitude and frequency. The frequency is estimated by a Kalman filter method. The estimation schemes require only voltage and current measurements. A power management system is developed to operate the battery storage in the DC-microgrid based on the wind generation. The control strategy operates under variable wind speed and variable load. The control, estimation and power management schemes are built in the MATLAB/Simulink and RT-LAB platforms and experimentally validated using the OPAL-RT real-time digital controller and a DC-microgrid experimental setup.
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Hu, Chunyang, Wenping Cao, and Bin Ning. "Visual servoing with deep reinforcement learning for rotor unmanned helicopter." International Journal of Advanced Robotic Systems 19, no. 2 (March 1, 2022): 172988062210848. http://dx.doi.org/10.1177/17298806221084825.
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Visual servoing is a key approach to achieve visual control for the rotor unmanned helicopter. The challenges of the inaccurate matrix estimation and the target loss restrict the performance of the visual servoing control systems. This work proposes a novel visual servoing controller using the deep Q-network to achieve an efficient matrix estimation. A deep Q-network learning agent learns a policy estimating the interaction matrix for visual servoing of a rotor unmanned helicopter using continuous observation. The observation includes a combination of feature errors. The current matrix and the desired matrix constitute the action space. A well-designed reward guides the deep Q-network agent to get a policy to generate a time-varying linear combination between the current matrix and the desired matrix. Then, the interaction matrix is calculated by the linear combination. The potential mapping between the observation and the interaction matrix is learned by cascading the deep neural network layers. Experimental results show that the proposed method achieves faster convergence and lower target loss probability in tracking than the visual servoing methods with the fixed parameter.
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Demir, Ridvan, and Murat Barut. "Novel hybrid estimator based on model reference adaptive system and extended Kalman filter for speed-sensorless induction motor control." Transactions of the Institute of Measurement and Control 40, no. 13 (November 28, 2017): 3884–98. http://dx.doi.org/10.1177/0142331217734631.
Full textAbstract:
This paper presents a novel hybrid estimator consisting of an extended Kalman filter (EKF) and an active power-based model reference adaptive system (AP-MRAS) in order to solve simultaneous estimation problems of the variations in stator resistance ([Formula: see text]) and rotor resistance ([Formula: see text]) for speed-sensorless induction motor control. The EKF simultaneously estimates the stator stationary axis components ([Formula: see text] and [Formula: see text]) of stator currents, the stator stationary axis components ([Formula: see text] and [Formula: see text]) of stator fluxes, rotor angular velocity ([Formula: see text]), load torque ([Formula: see text]) and [Formula: see text], while the AP-MRAS provides the online [Formula: see text] estimation to the EKF. Both the AP-MRAS, whose adaptation mechanism is developed with the help of the least mean squares method in this paper, and the EKF only utilize the measured stator voltages and currents. Performances of the proposed hybrid estimator in this paper are tested by challenging scenarios generated in simulations and real-time experiments. The obtained results demonstrate the effectiveness of the introduced hybrid estimator, together with a [Formula: see text] reduction in the processing time and size of the estimation algorithm in terms of previous studies performing the same estimations of the states and parameters. From this point of view, it is the first such study in the literature, to our knowledge.
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Liu, Jun, and Qiao Sun. "Vibration Control of a Nonlinear Rotor System through Electro-Magnetic Bearings." Advanced Materials Research 452-453 (January 2012): 1408–14. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.1408.
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In rotating machinery, vibration resonance with large amplitude and complex pattern occurs at critical speeds due to rotor imbalance and nonlinear effects. In this paper, a vibration control method is proposed for a rotor system supported by a ball bearing and an electro-magnetic bearing. In particular, a disturbance observer combined with the current delay estimation is implemented to improve the controller's ability of compensating for system's nonlinear effects and uncertainty. As a result, the rotor vibration is suppressed to very small amplitudes in the entire operating speed range. The proposed method is validated through numerical simulations and experiments.
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Achari, K. Narasimhaiah, D. V. Ashok Kumar, and M. Vijaya Kumar. "Sensorless Control of IPMSM Drive using EKF with Electromegnetic Noise Effect." International Journal of Power Electronics and Drive Systems (IJPEDS) 9, no. 1 (March 1, 2018): 157. http://dx.doi.org/10.11591/ijpeds.v9.i1.pp157-165.
Full textAbstract:
This paper proposes a new move toward to assess the performance of sensorless control of interior permanent magnet synchronous motor (IPMSM) drive along with electromagnetic noise effect by using EKF. Normally in rotary condition, rotor position and speed estimation of IPMSM drive are drawn through an Extended Kalman Filter (EKF) algorithm by measuring its voltages and currents of the stator. The main drawback in developing EKF is it may not proficient to consider the effect of electromagnetic noise which is mainly produced during the time of different speed ranges. Owing to this reason this may cause to vary the motor flux linkages which are significant to find the rotor position and speed by EKF method will give approximate results. To carry on this process, we present the simulation results for sensorless speed control of IPMSM drive by using EKF algorithm with the incorporation of a noise signal which is corresponding to the frequency of electromagnetic noise signal using MATLAB/Simulink software. The armature current, rotor position, and speed estimation are analyzed under this noise signal effect and the effectiveness of the EKF for sensorless control of IPMSM drive is observed.
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Saifi, R. "Implementation of a new flux rotor based on model reference adaptive system for sensorless direct torque control modified for induction motor." Electrical Engineering & Electromechanics, no. 2 (March 5, 2023): 37–42. http://dx.doi.org/10.20998/2074-272x.2023.2.06.
Full textAbstract:
Introduction. In order to realize an efficient speed control of induction motor, speed sensors, such as encoder, resolver or tachometer may be utilized. However, some problems appear such as, need of shaft extension, which decreases the mechanical robustness of the drive, reduce the reliability, and increase in cost. Purpose. In order to eliminate of speed sensors without losing. Several solutions to solve this problem have been suggested. Based on the motor fundamental excitation model, high frequency signal injection methods. The necessity of external hardware for signal injection and the adverse influence of injecting signal on the motor performance do not constitute an advantage for this technique. Fundamental model-based strategies method using instantaneous values of stator voltages and currents to estimate the rotor speed has been investigate. Several other methods have been proposed, such as model reference adaptive system, sliding mode observers, Luenberger observer and Kalman filter. The novelty of the proposed work consists in presenting a model reference adaptive system based speed estimator for sensorless direct torque control modified for induction motor drive. The model reference adaptive system is formed with flux rotor and the estimated stator current vector. Methods. The reference model utilizes measured current vector. On the other hand, the adjustable model uses the estimated stator current vector. The current is estimated through the solution of machine state equations. Practical value. The merits of the proposed estimator are demonstrated experimentally through a test-rig realized via the dSPACE DS1104 card in various operating conditions. The experimental results show the efficiency of the proposed speed estimation technique. Experimental results show the effectiveness of the proposed speed estimation method at nominal speed regions and speed reversal, and good results with respect to measurement speed estimation errors obtained.
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Marques, Gil Domingos, and Duarte Mesquita e Sousa. "A New Sensorless MRAS Based on Active Power Calculations for Rotor Position Estimation of a DFIG." Advances in Power Electronics 2011 (May 23, 2011): 1–8. http://dx.doi.org/10.1155/2011/970364.
Full textAbstract:
A sensorless method for the estimation of the rotor position of the wound-rotor induction machine is described in this paper. The method is based on the MRAS methodology and consists in the comparison of two models for the evaluation of the active power transferred across the air gap: the reference model and the adaptive model. The reference model obtains the power transferred across the air gap using directly available and measured stator variables. The adaptive model obtains the same quantity in function of electromotive forces and rotor currents that are measurable on the rotor position, which is under estimation. The method does not need any information about the stator or rotor flux and can be implemented in the rotor or in the stator reference frames with a hysteresis or with a PI controller. The stability analysis gives an unstable region on the rotor current dq plane. Simulation and experimental results show that the method is appropriate for the vector control of the doubly fed induction machine under the stability region.
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Li, Yu Dong, Bo Zhou, Ying Liu, and Cheng Liang Zhao. "Analysis and Simulation of Low Speed Sensorless Vector Control with Two Current Signal Injection Schemes." Advanced Materials Research 722 (July 2013): 361–68. http://dx.doi.org/10.4028/www.scientific.net/amr.722.361.
Full textAbstract:
Two current signal injection methods, the fluctuating high frequency (HF) current signal injection and low frequency (LF) current signal injection, were discussed. The basic principles of rotor position self-sensing using these current signal injection and the key techniques in implementation were presented and the simulation models for sensorless vector control systems of a permanent magnet synchronous motor (PMSM) were established using two proposed rotor position estimation methods. Comparative simulation study of the fluctuating HF current signal injection and LF current signal injection was investigated, and draw the conclusions that the saliency-tracking scheme using fluctuating HF current signal injection possesses simpler configuration and better speed-adjustable performance both in static and dynamic.
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Varga, Toni, Tin Benšić, Vedrana Jerković Štil, and Marinko Barukčić. "Continuous Control Set Predictive Current Control for Induction Machine." Applied Sciences 11, no. 13 (July 5, 2021): 6230. http://dx.doi.org/10.3390/app11136230.
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A speed tracking control method for induction machine is shown in this paper. The method consists of outer speed control loop and inner current control loop. Model predictive current control method without the need for calculation of the weighing factors is utilized for the inner control loop, which generates a continuous set of voltage reference values that can be modulated and applied by the inverter to the induction machine. Interesting parallels are drawn between the developed method and state feedback principles that helped with the analysis of the stability and controllability. Simple speed and rotor flux estimator is implemented that helps achieve sensorless control. Simulation is conducted and the method shows great performance for speed tracking in a steady state, and during transients as well. Additionally, compared to the finite control set predictive current control, it shows less harmonic content in the generated torque on the rotor shaft.
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Fang, Jin Xiang. "Position Sensorless Control of Brushless DC Motor." Advanced Materials Research 915-916 (April 2014): 418–21. http://dx.doi.org/10.4028/www.scientific.net/amr.915-916.418.
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According to the chattering problem in the traditional sliding mode observer of the position sensorless control of brushless DC motor, a novel quasi sliding mode observer for rotor position estimation was proposed, which took the error between the actual and estimated currents as sliding surface and tracked the actual rotor position according to the mathematical relationship of back EMF and speed of the motor. Then the sensorless control system of the brushless DC motor based on the novel sliding mode observer was designed. Simulation results showed that the novel sliding mode control method could improve the rotor position estimation accuracy and effectively suppress the chattering problem to enhance the robustness of system.
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Adamczyk, Michał. "Rotor Resistance Estimator based on Virtual Current Sensor Algorithm for Induction Motor Drives." Power Electronics and Drives 5, no. 1 (January 1, 2020): 143–56. http://dx.doi.org/10.2478/pead-2020-0008.
Full textAbstract:
Abstract In this article, model reference adaptive system (MRAS)-based estimator of a rotor resistance of an induction motor (IM) is presented. In contrast to the solutions known from the literature, the reference model of this estimator uses the measured values of the phase current and the adaptive part is a virtual current sensor. The article presents an accurate description of the algorithm taking into account the discrete equations for possible practical implementation in the microprocessor system. In the first step, the impact of motor parameters to stator current estimation quality in the adaptive model was checked. Subsequently, simulation tests of the proposed rotor resistance estimator were carried out for the field-oriented control of the induction motor drive system with a model of an induction motor with fixed parameters and an induction motor with a changing main inductance according to a magnetisation curve. The analysis of the estimator’s work showed its high efficiency and insensitivity to changes in the IM main inductance.
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Gunabalan, R., P. Sanjeevikumar, Frede Blaabjerg, Patrick W. Wheeler, Olorunfemi Ojo, and Ahmet H. Ertas. "Speed sensorless vector control of parallel-connected three-phase two-motor single-inverter drive system." FACETS 1, no. 1 (March 1, 2017): 1–16. http://dx.doi.org/10.1139/facets-2015-0004.
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This paper presents the characteristic behavior of direct vector control of two induction motors with sensorless speed feedback having the same rating parameters, paralleled combination, and supplied from a single current-controlled pulse-width-modulated voltage-source inverter drive. Natural observer design technique is known for its simple construction, which estimates the speed and rotor fluxes. Load torque is estimated by load torque adaptation and the average rotor flux was maintained constant by rotor flux feedback control. The technique’s convergence rate is very fast and is robust to noise and parameter uncertainty. The gain matrix is absent in the natural observer. The rotor speed is estimated from the load torque, stator current, and rotor flux. Under symmetrical load conditions, the difference in speed between two induction motors is reduced by considering the motor parameters as average and difference. Rotor flux is maintained constant by the rotor flux control scheme with feedback, and the estimation of rotor angle is carried out by the direct vector control technique. Both balanced and unbalanced load conditions are investigated for the proposed AC motor drive system. Experimental results presented in this paper show good agreement with the theoretical formulations.
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Echeikh, H., R. Trabelsi, Atif Iqbal, M. F. Mimouni, and R. Alammari. "Online Adaptation of Rotor Resistance based on Sliding Mode Observer with Backstepping Control of A Five-Phase Induction Motor Drives." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 3 (September 1, 2016): 648. http://dx.doi.org/10.11591/ijpeds.v7.i3.pp648-655.
Full textAbstract:
Multiphase electric drives have been developed due to numerous advantages offered by those machines when it compared with the conventional three-phase machines. Multiphase motor drives are considered for applications, where the reduction of power per phase for both motor and inverter and high reliability are required. High performance control techniques are developed for multi-phase drives. The performances of the high performance controller and flux observers may be degraded during the operation. Since the parameters of Induction Motor (IM) varies continuously due to temperature variation and heating. Thus it is significantly important that the value of rotor resistance is continuously observed online and adapted by the control algorithm in order to avoid detuning effects. The efficiency and performance of an induction motor drive system can be improved by online observation of the critical parameters, such as the rotor resistance and stator resistance. Among the parameters of IM, rotor resistance is a decisive one for flux estimation, and also the stator resistance becomes critical in the low-speed operation condition. This paper presents a new online estimation method for the rotor resistance of the IM for sliding mode observer. This method generally based on theories of variable structure and is useful in order to adjust online unknown parameters (load torque and rotor resistance). The presented non-linear compensator afford a voltage inputs on the articulation of stator current and rotor speed measurements, and engender an estimates for the unknown parameters simultaneously, the non-measurable state variables (rotor flux and derivatives of the stator current and voltage) that converge to the corresponding true values. Under the persistent excitation condition, the proposed method estimates the actual value of rotor resistance, which guarantees the exact estimation of the rotor flux. Non-linear Backstepping control and adaptive sliding mode observer of a five-phase induction motor drive is presented. The accuracy and validity of the method is verified by MATLAB simulation model.
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Trujillo Guajardo, Luis Alonso, Miguel Angel Platas Garza, Johnny Rodríguez Maldonado, Mario Alberto González Vázquez, Luis Humberto Rodríguez Alfaro, and Fernando Salinas Salinas. "Prony Method Estimation for Motor Current Signal Analysis Diagnostics in Rotor Cage Induction Motors." Energies 15, no. 10 (May 11, 2022): 3513. http://dx.doi.org/10.3390/en15103513.
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This article presents an evaluation of Prony method and its implementation considerations for motor current signal analysis diagnostics in rotor cage induction motors. The broken rotor bar fault signature in current signals is evaluated using Prony method, where its advantages in comparison with fast Fourier transform are presented. The broken rotor bar fault signature could occur during the life cycle operation of induction motors, so that is why an effective early detection estimation technique of this fault could prevent an insulation failure or heavy damage, leaving the motor out of service. First, an overview of cage winding defects in rotor cage induction motors is presented. Next, Prony method and its considerations for the implementation in current signature analysis are described. Then, the performance of Prony method using numerical simulations is evaluated. Lastly, an assessment of Prony method as a tool for current signal analysis diagnostics is performed using a laboratory test system where real signals of an induction motor with broken rotor bar operated with/without a variable frequency drive are analyzed. The summary results of the estimation (amplitudes and frequencies) are presented in the results and discussion section.
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Sepeeh, Muhamad Syazmie, Shamsul Aizam Zulkifli, Sy Yi Sim, Huang-Jen Chiu, and Mohd Zamri Che Wanik. "Speed Tracking for IFOC Induction Motor Speed Control Using Hybrid Sensorless Speed Estimator Based on Flux Error for Electric Vehicles Application." Machines 10, no. 11 (November 17, 2022): 1089. http://dx.doi.org/10.3390/machines10111089.
Full textAbstract:
This paper presents hybrid sensorless speed tracking by an indirect field-oriented control (IFOC) for an induction motor (IM). The sensorless model is based on an improved virtual estimation topology model to predict the virtual speed and flux of the IM using stator current components. The hybrid sensorless model, defined as a modification of voltage with a rotor flux-oriented current model, was also implemented with proportional-integral (PI) control for comparison with the conventional voltage model (CVM). The suggested adaptive mechanism for PI control in the hybrid estimator was able to compensate for the back-EMF error from the rotor flux-oriented current model into the voltage model and change the air gap flux of the IM. An accurate rotor flux position was estimated and used to estimate the speed with low speed error. This IFOC model, with various speed change references, was tested in a simulation environment by using the MATLAB/Simulink program. The proposed hybrid estimator was tested in two different EV operations, which were reverse and forward operations. The effectiveness of the proposed estimator was analyzed for its transient and steady-state performances based on settling time, recovery time and the overshoot and speed error percentages. All the results were in good agreement in terms of the stability of the speed and current controller with minimum speed error obtained, where the average errors were 0.08% and 0.16% for high speed and lower speed, respectively.
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Heidari, Hamidreza, Anton Rassõlkin, Mohammad Hosein Holakooie, Toomas Vaimann, Ants Kallaste, Anouar Belahcen, and Dmitry V. Lukichev. "A Parallel Estimation System of Stator Resistance and Rotor Speed for Active Disturbance Rejection Control of Six-Phase Induction Motor." Energies 13, no. 5 (March 2, 2020): 1121. http://dx.doi.org/10.3390/en13051121.
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In this paper, a parallel estimation system of the stator resistance and the rotor speed is proposed in speed sensorless six-phase induction motor (6PIM) drive. First, a full-order observer is presented to provide the stator current and the rotor flux. Then, an adaptive control law is designed using the Lyapunov stability theorem to estimate the rotor speed. In parallel, a stator resistance identification scheme is proposed using more degrees of freedom of the 6PIM, which is also based on the Lyapunov stability theorem. The main advantage of the proposed method is that the stator resistance adaptation is completely decoupled from the rotor speed estimation algorithm. To increase the robustness of the drive system against external disturbances, noises, and parameter uncertainties, an active disturbance rejection controller (ADRC) is introduced in direct torque control (DTC) of the 6PIM. The experimental results clarify the effectiveness of the proposed approaches.
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Liao, Guangliang, Wei Zhang, and Chuan Cai. "Research on a PMSM control strategy for electric vehicles." Advances in Mechanical Engineering 13, no. 12 (December 2021): 168781402110514. http://dx.doi.org/10.1177/16878140211051462.
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This paper proposes a novel state estimation based permanent magnet synchronous motor (PMSM) control method for electric vehicle (EV) driving. Firstly, a state feedback decoupling control with disturbance feed-forward (SFDCDF) is described. As motor angular speed and rotary angle are key information for the proposed control algorithm and park’s transformation, a novel observer based angular speed estimator (OBASE) is proposed for angular speed estimation. Moreover, an extended Kalman filter (EKF) based rotary angle estimator (EBRAE) is used for rotary angle estimation with information of the estimated angular speed. The convergence of angular speed estimation is proven through Lyapunov stability theory. Simulation results also indicate that the proposed algorithms can control PMSM torque, current, and angular speed to accurately follow reference values without severe fluctuation. In addition, in order to provide SFDCDF with load torque information, the OBASE is slightly modified to work as a vehicle load estimator (VLE) so PMSM responds more rapidly and speed fluctuates more slightly when the load suddenly changes. Then a series of hardware in the loop (HIL) simulations are carried out. Results indicate that the proposed control strategy can precisely estimate PMSM’s angular speed and rotor angle. Also, it can improve the driving performance of PMSM used on EVs.
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Lopac, Nikola, Neven Bulic, and Niksa Vrkic. "Sliding Mode Observer-Based Load Angle Estimation for Salient-Pole Wound Rotor Synchronous Generators." Energies 12, no. 9 (April 27, 2019): 1609. http://dx.doi.org/10.3390/en12091609.
Full textAbstract:
Synchronous generator load angle is a fundamental quantity for power system stability assessment, with possible real-time applications in protection and excitation control systems. Commonly used methods of load angle determination require additional measuring equipment, while existing research on load angle estimation for wound rotor synchronous generator has been limited to the estimator based on the generator’s phasor diagram and estimators based on artificial neural networks. In this paper, a load angle estimator for salient-pole wound rotor synchronous generator, based on a simple sliding mode observer (SMO) which utilizes field current, stator voltages, and stator currents measurements, is proposed. The conventional SMO structure is improved with use of hyperbolic tangent sigmoid functions, implementation of the second order low-pass filters accompanied with corresponding phase delay compensation, and introduction of an adaptive observer gain proportional to the measured field current value. Several case studies conducted on a generator connected to a power system suggest that the proposed estimator provides an adequate accuracy during active and reactive power disturbances during stable generator operation, outperforming the classical phasor diagram-based estimator by reducing mean squared error by up to 14.10%, mean absolute error by up to 41.55%, and maximum absolute error by up to 8.81%.
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Abo-Khalil, Ahmed G., Ali M. Eltamaly, Praveen R.P., Ali S. Alghamdi, and Iskander Tlili. "A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems." Sustainability 12, no. 20 (October 14, 2020): 8481. http://dx.doi.org/10.3390/su12208481.
Full textAbstract:
Currently, among the topologies of wind energy conversion systems, those based on full power converters are growing. The permanent magnet synchronous generator (PMSG) uses full power converter to allow wide speed ranges to extract the maximum power from the wind. In order to obtain efficient vector control in a synchronous generator with permanent magnets, it is necessary to know the position of the rotor. The PMSGs work over a wide range of speed, and it is mandatory to measure or estimate their speed and position. Usually, the position of the rotor is obtained through Resolver or Encoder. However, the presence of these sensor elements increases the cost, in addition to reducing the system’s reliability. Moreover, in high wind power turbine, the measured wind speed by the anemometer is taken at the level of the blades which makes the measurement of the wind speed at a single point inaccurate. This paper is a study on the sensorless control that removes the rotor position, speed sensors and anemometer from the speed control. The estimation of the rotor position is based on the output of a rotor current controller and the wind speed estimator is based on the opposition-based learning (OBL), particle swarm optimization and support vector regression.
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Yang, Weibin, Yuanlin Wang, Hao Guo, Xinxin Sun, Gurakuq Dajaku, Saleem Riaz, Haider Zaman, and Dieter Gerling. "Torque-Pulse-Based Initial Rotor Polarity Detection for IPMSM with Low Saturation Effect." Electronics 11, no. 24 (December 13, 2022): 4165. http://dx.doi.org/10.3390/electronics11244165.
Full textAbstract:
Referring to the sensorless control of interior permanent magnet synchronous motor (IPMSM), the initial rotor polarity is normally estimated based on the motor saturation effect. However, for certain special IPMSMs, the saturation effect is weak even at the rated point, making the saturation-based rotor polarity detection methods invalid. Therefore, this paper proposes a novel rotor polarity detection method based on torque-pulse injection. Two current pulses are imposed on the positive and negative directions of the q-axis estimated by the high-frequency injection (HFI) method, respectively; the signs of speed peaks indicate the rotor polarity. To derive the rotor polarity from the tiny speed signal, a new speed estimation method is presented. To improve the dynamic performance of speed estimation, a special current filter is adopted in the HFI method. To choose the proper width and amplitude of the current pulse under different load and inertia conditions, an automatic program is designed. The proposed method has the advantages of high accuracy, short identification time, tiny movement, and automatic operation, making it applicable to various load and inertia conditions. The effectiveness of the proposed method is validated by experiments on an IPMSM with low saturation effect.
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Tarchała and Wolkiewicz. "Performance of the Stator Winding Fault Diagnosis in Sensorless Induction Motor Drive." Energies 12, no. 8 (April 21, 2019): 1507. http://dx.doi.org/10.3390/en12081507.
Full textAbstract:
This paper deals with the diagnosis of stator winding inter-turn faults for an induction motor drive operating without a speed sensor in a speed-sensorless mode. The rotor direct field oriented control structure (DFOC) was applied, its reference current and voltage component values were analyzed, and their selected harmonics were applied as effective fault indicators. To ensure robust speed estimation, a sliding mode model reference adaptive system (SM-MRAS) estimator was selected. The influence of load torque, reference speed, proportional-integral (PI) controller parameters, and short-circuit current on fault diagnosis and speed estimation performance was verified. Experimental test results obtained for a 3 kW induction motor drive are included.