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Journal articles on the topic 'Speed sensorless control'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Usama, Muhammad, and Jaehong Kim. "Robust adaptive observer-based finite control set model predictive current control for sensorless speed control of surface permanent magnet synchronous motor." Transactions of the Institute of Measurement and Control 43, no. 6 (January 10, 2021): 1416–29. http://dx.doi.org/10.1177/0142331220979264.

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The objective of the paper is to present the efficient and dynamic sensorless speed control of a surface permanent magnet synchronous motor (SPMSM) drive at a wide speed range. For high-performance speed sensorless control, a finite control set model predictive current control (FCS-MPCC) algorithm based on a model reference adaptive system (MRAS) is proposed. With the FCS-MPCC algorithm, the inner current control loop is eliminated, and the limitations of the cascaded linear controller are overcome. The proposed speed sensorless control algorithm provides an efficient speed control technique for the SPMSM drive owing to its fast dynamic response and simple principle. The adaptive mechanism is adopted to estimate the rotor shaft speed and position used in FCS-MPCC for dynamic sensorless control. FCS-MPCC uses a square cost function to determine the optimal output voltage vector (VV) from the switching states that give the low cost index. A discrete-time model of a system is used to predict future currents across all the feasible VVs produced by the voltage source inverter. The VV that reduced the cost function is adopted and utilized. Simulation results showed the efficacy of the presented scheme and the viability of the proposed sensorless speed control design under various load conditions at a wide speed operation range.

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2

Pham, Ngoc Thuy. "Sensorless speed control of SPIM using BS_PCH novel control structure and NNSM_SC MRAS speed observer." Journal of Intelligent & Fuzzy Systems 39, no. 3 (October 7, 2020): 2657–77. http://dx.doi.org/10.3233/jifs-190540.

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This paper propose a novel Port Controlled Hamiltonian_Backstepping (PCH_BS) control structure with online tuned parameters, in combination with the modified Stator Current Model Reference Adaptive Syatem (SC_MRAS) based on speed and flux estimator using Neural Networks(NN) and sliding mode (SM) for sensorless vector control of the six phase induction motor (SPIM). The control design is based on combination PCH and BS techniques to improve its performance and robustness. The combination of BS_PCH controller with speed estimator can compensate for the uncertainties caused by the machine parameter variations, measurement errors, and external load disturbances, enables very good static and dynamic performance of the sensorless drive system (perfect tuning of the speed reference values, fast response of the motor current and torque, high accuracy of speed regulation) in a wide speed range, and robust for the disturbances of the load, the speed variation and low speed. The proposed sensorless speed control scheme is validated through Matlab-Simulink. The simulation results verify the effectiveness of the proposed control and observer.

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3

Uyulan, Caglar. "A robust-adaptive linearizing control method for sensorless high precision control of induction motor." Measurement and Control 52, no. 5-6 (April 15, 2019): 634–56. http://dx.doi.org/10.1177/0020294019833072.

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Even if there exists remarkable applications of induction machines in variable speed drives and also in speed sensorless control in the low–high speed region, open/closed loop estimators in the literature utilized on induction machine sensorless position control vary regarding to their accuracies, sensitivity, and robustness with respect to the variation of model parameter. The deterioration of dynamic performance depends on the lack of estimation techniques which provide trustable information on the flux or speed/position over a wide speed range. An effective estimator should handle the high number of parameter and model uncertainties inherent to induction machines and also torque ripple, the compensation of which is crucial for a satisfactory decoupling and linearizing control to provide the accuracy and precision requirements of demanding motion control in the field of robotics/unmanned vehicle. In this study, to address all of the above-mentioned problems, robust-adaptive linearizing schemes for the sensorless position control of induction machines based on high-order sliding modes and robust differentiators to improve performance were designed. The control schemes based on direct vector control and direct torque control are capable of torque ripple attenuation taking both space and current harmonics into account. The simulation results comprise both the estimation and sensorless speed control of induction machines over a wide operation range, especially at low and zero speed, all of which are promising and indicate significant superiority over existing solutions in the literature for the high precision, direct-drive, speed/position sensorless control of squirrel-cage induction machines.

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4

Hirano, Koichi, Hidehiro Hara, Teruo Tsuji, and Ryuichi Oguro. "Sensorless Speed Control of IPM Motor." IEEJ Transactions on Industry Applications 120, no. 5 (2000): 666–72. http://dx.doi.org/10.1541/ieejias.120.666.

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5

Jezernik, Karel. "Vss Speed Sensorless Control of PMSM." IFAC Proceedings Volumes 41, no. 2 (2008): 1815–20. http://dx.doi.org/10.3182/20080706-5-kr-1001.00310.

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6

Zhang, Yong, and Xu-Feng Cheng. "Sensorless Control of Permanent Magnet Synchronous Motors and EKF Parameter Tuning Research." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/3916231.

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This paper concerns the parameter tuning and the estimated results postprocessing of the extended Kalman filter for the sensorless control application of permanent magnet synchronous motors. At first an extended Kalman filter parameter tuning method is proposed based on the theoretical and simulation analysis of extended Kalman filter parameters. Furthermore, a sensorless control system is proposed based on the parameter tuning method and the simulation analysis of extended Kalman filter estimation results in different reference speeds and different load torques. The proposed sensorless control system consists of two parts. The first one is a module to self-regulate extended Kalman filter parameters. The second part can correct the estimated speed and the estimated rotation angle based on the reference speed and the electromagnetic torque. Finally, simulation results are presented to verify the feasibility and validity of the proposed sensorless control system.

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7

Asfu, Workagegn Tatek. "Stator Current-Based Model Reference Adaptive Control for Sensorless Speed Control of the Induction Motor." Journal of Control Science and Engineering 2020 (October 14, 2020): 1–17. http://dx.doi.org/10.1155/2020/8954704.

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This paper described that the stator current-based model reference adaptive system (MRAS) speed estimator is used for the induction motor (IM) indirect vector speed control without a mechanical speed sensor. Due to high sensitivity of motor parameters variation at low speed including zero, stability analysis of MRAS design is performed to correct any mismatch parameters value in the MRAS performed to estimate the motor speed at these values. As a result, the IM sensorless control can operate over a wide range including zero speed. The performance of the stator current-based MRAS speed estimator was analyzed in terms of speed tracking capability, torque response quickness, low speed behavior, step response of drive with speed reversal, sensitivity to motor parameter uncertainty, and speed tracking ability in the regenerative mode. The system gives a good performance at no-load and loaded conditions with parameter variation. The stator current-based MRAS estimator sensorless speed control technique can make the hardware simple and improve the reliability of the motor without introducing a feedback sensor, and it becomes more important in the modern AC IM. The sensorless vector control operation has been verified by simulation on Matlab and experimentally using Texas Instruments HVMTRPFCKIT with TMS320 F28035 DSP card and 0.18 kw AC IM.

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8

Pujar, Jagadish H., and S. F. Kodad. "A Novel Fuzzy Adaptive Speed Estimator for Space Vector Modulated DTFC of AC Drives." Advanced Materials Research 403-408 (November 2011): 4850–58. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4850.

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In this paper a novel sensorless speed control scheme of Induction Motor (IM) by means of Direct Torque Fuzzy Control (DTFC), PI-type fuzzy speed regulator and fuzzy based Model Reference Adaptive Systems (MRAS) speed estimator strategies has been proposed, which seems to be a boom in sensorless speed control schemes of AC drives. Normally, the conventional sensorless speed control performance of IM drive deteriorates at low speed. Hence the attention has been focused to improve the performance of the IM drive at low speed range as well, by implementing fuzzy control strategies. So, this research work describes a novel adaptive fuzzy based speed estimation mechanism which replaces the conventional PI controller used in MRAS adaptation mechanism. The proposed scheme is validated through extensive numerical simulations on MATLAB. The simulated results signify that the proposed control scheme provides satisfactory high dynamic performance and robustness during low speed operations of IM drive compare to conventional sensorless speed estimator of DTFC scheme.

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9

Tavares Câmara, Helder, Rafael Cardoso, Rodrigo Zelir Azzolin, and Hilton Abílio Gründling. "Low-cost Sensorless Induction Motor Speed Control." Eletrônica de Potência 12, no. 3 (November 1, 2007): 233–43. http://dx.doi.org/10.18618/rep.2007.3.233243.

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10

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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11

Wang, Hong Yu, Wen Long Cai, and Cheng Wei Hou. "Speed Sensorless Vector Control System of Induction Motor." Advanced Materials Research 516-517 (May 2012): 1664–67. http://dx.doi.org/10.4028/www.scientific.net/amr.516-517.1664.

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This paper introduces a vector control system for speed sensorless induction motor drive, which we have recently developed. In the introduce vector control system, one induction motor’s rotor speed estimation method based on model reference adaptive identification theory is proposed. The induction motor speed identification system based on the proposed method can estimate the rotor speed of the induction motor. The speed sensorless vector control system based on proposed method in this paper was built with Simulink blocks in Matlab platform. The simulation results indicate that the proposed method could operate stably in whole range of speed with preferable identification precision of rotor speed.

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12

Georgiev, Tsolo, and Mikho Mikhov. "A Sensorless Speed Control System for DC Motor Drives." Scientific Journal of Riga Technical University. Power and Electrical Engineering 25, no. 25 (January 1, 2009): 155–58. http://dx.doi.org/10.2478/v10144-009-0033-z.

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A Sensorless Speed Control System for DC Motor DrivesAn approach to sensorless speed control of permanent magnet DC motor drives is presented in this paper. The motor speed has been estimated indirectly by the respective back EMF voltage. Using a discrete vector-matrix description of the controlled object, an optimal modal state observer has been synthesized, as well as an optimal modal controller. The results obtained show that the applied control method can ensure good performance.

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13

Lu, An, and Kay Hameyer. "A comparative study of sensorless speed control." International Journal of Applied Electromagnetics and Mechanics 39, no. 1-4 (September 5, 2012): 787–91. http://dx.doi.org/10.3233/jae-2012-1543.

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14

Kawaji, Shigeyasu, Fuminori Ozaki, and Ryutaro Higashi. "Sensorless Force Control for High-speed Pressurization." Journal of Robotics and Mechatronics 13, no. 3 (June 20, 2001): 222–29. http://dx.doi.org/10.20965/jrm.2001.p0222.

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Force control technology needs a breakthrough to be used for practical purposes because it is rarely used in the industry although it is being improved in academic circles. We propose solving problems of conventional position control in pressurization using high-speed sensorless force control for the IC testing handler used in semiconductor manufacturing. The key techniques to solve the problem are piecewise polynomial trajectory generation to meet needs for high-speed operation, a model-following force servo to achieve pressurizing conditions, and a disturbance observer to estimate pressurization. The effectiveness of the proposed method is confirmed in experiments.

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15

Jiao, Zhi. "Speed Sensorless Control System Based on MRAS." Applied Mechanics and Materials 742 (March 2015): 586–89. http://dx.doi.org/10.4028/www.scientific.net/amm.742.586.

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In this paper, a strategy for estimating the induction motor’s rotor speed is proposed. The proposed rotor speed estimation strategy is based on model reference adaptive identification theory. By applying the proposed strategy, the induction motor control system can estimate the induction motor's rotor speed precisely. To improve the rotor speed estimation performance of the system, two methods have been adopt. The speed sensorless control system based on proposed strategy was built with Simulink blocks in Matlab platform. The corresponding simulation results demonstrate that the proposed method can operate stably in the whole range of speed with preferable estimation precision of stator resistance and rotor speed.

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16

Edelbaher, G., K. Jezernik, and E. Urlep. "Low-speed sensorless control of induction Machine." IEEE Transactions on Industrial Electronics 53, no. 1 (February 2006): 120–29. http://dx.doi.org/10.1109/tie.2005.862307.

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17

Yu, Hai Fang, Peng Gao, and Shun Jie Han. "Efficiency Optimization in Speed-Sensorless Control of Induction Motors." Applied Mechanics and Materials 672-674 (October 2014): 1214–18. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1214.

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An efficiency optimization model for induction motors with speed-sensorless control is presented in this paper. An mathematical loss model with stator iron loss in DTC(Direct Torque Control) system is used to calculate the motors loss, the loss efficiency and the optimal flux. Additionally, the efficiency optimization control strategy combined with the speed-sensorless model is used to rebuild the simulation modeling. The simulation results with the proposed control strategy show superior effects compared to the traditional control methods. The optimal control strategy can be achieved to improve the motor efficiency.

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18

Abu-Rub, H., D. Stando, and M. P. Kazmierkowski. "Simple speed sensorless DTC-SVM scheme for induction motor drives." Bulletin of the Polish Academy of Sciences: Technical Sciences 61, no. 2 (June 1, 2013): 301–7. http://dx.doi.org/10.2478/bpasts-2013-0028.

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Abstract The paper focuses on the development of a novel DSP based high performance speed sensorless control scheme for PWM voltage source inverter fed induction motor drives. Firstly, two generic torque and flux control methods the Field Oriented Control (FOC) and Direct Torque Control (DTC), are briefly described. For implementation the sensorless scheme DTC with Space Vector Modulation (DTCSVM) has been selected because it eliminates the disadvantages associated with the DTC while keeping the advantages of both FOC and DTC. Secondly, the simple flux vector observer allowing speed sensor elimination is given. The novelty of the presented system lays in combining the DTC-SVM structure with a simple observer for both torque/flux and speed sensorless control. Furthermore, the DTC-SVM structure which operates in speed sensorless and torque control mode is presented. Finally, the description of a 50 kW laboratory drive and experimental results illustrating properties of the system are given.

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19

Leppanen, V. M., and J. Luomi. "Speed-Sensorless Induction Machine Control for Zero Speed and Frequency." IEEE Transactions on Industrial Electronics 51, no. 5 (October 2004): 1041–47. http://dx.doi.org/10.1109/tie.2004.834965.

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20

Halvaei Niasar, Abolfazl, and Hossein Rahimi Khoei. "Sensorless Direct Power Control of Induction Motor Drive Using Artificial Neural Network." Advances in Artificial Neural Systems 2015 (March 30, 2015): 1–9. http://dx.doi.org/10.1155/2015/318589.

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This paper proposes the design of sensorless induction motor drive based on direct power control (DPC) technique. It is shown that DPC technique enjoys all advantages of pervious methods such as fast dynamic and ease of implementation, without having their problems. To reduce the cost of drive and enhance the reliability, an effective sensorless strategy based on artificial neural network (ANN) is developed to estimate rotor’s position and speed of induction motor. Developed sensorless scheme is a new model reference adaptive system (MRAS) speed observer for direct power control induction motor drives. The proposed MRAS speed observer uses the current model as an adaptive model. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Simulink. Some simulations are carried out for the closed-loop speed control systems under various load conditions to verify the proposed methods. Simulation results confirm the performance of ANN based sensorless DPC induction motor drive in various conditions.

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21

Gao, Jun Li, Shi Jun Chen, and Guo Cai Li. "Design of Sensorless Vector Control System for Induction Motors." Applied Mechanics and Materials 58-60 (June 2011): 2046–50. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2046.

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Online identification of motor rotor speed by using modified rotor flux orientation angle estimator and model reference adaptive system achieves sensorless vector control of induction motor. The principle verification conducted on self-developed sensorless vector control of induction motor shows that the system has good dynamic & static performance and induction motor achieves significant improvement in speed regulation in the premise of not adding cost of general inverters.

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22

Ram, Ganapathy, and Santha K R. "Review of Sliding Mode Observers for Sensorless Control of Permanent Magnet Synchronous Motor Drives." International Journal of Power Electronics and Drive Systems (IJPEDS) 9, no. 1 (March 1, 2018): 46. http://dx.doi.org/10.11591/ijpeds.v9.i1.pp46-54.

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Permanent magnet synchronous motors (PMSMs) are increasingly used in high performance variable speed drives of many industrial applications. PMSM has many features, like high efficiency, compactness, high torque to inertia ratio, rapid dynamic response, simple modeling and control, and maintenance free operation. Presence of position sensors 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. Advantages of sensorless control are 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. Moreover, the noises of system and measurements are considered other main problems. This paper presents a comprehensive study of the different sliding mode observer methods of speed and position estimations for sensorless control of PMSM drives.

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23

Yang, Ling Xiao, and Jing Zhang. "Simulation Research of Vector Control System Based on the Improved MRAS Speed Sensorless." Applied Mechanics and Materials 273 (January 2013): 419–23. http://dx.doi.org/10.4028/www.scientific.net/amm.273.419.

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According to the basic principle of vector control for the asynchronous motor, a speed sensorless vector control system of asynchronous motor is bulit which based on the Model Reference Adaptive System (MRAS) theory. The traditional MRAS speed identification algorithm is vulnerable to the effects of stator resistance, an improved method of MRAS speed identification is put forward. A simulation model of the speed sensorless vector control system based on MRAS is bulit in Matlab/simulink, the simulation results show that the speed estimation method can accurately calculate the speed of motor.

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24

Verrelli, Cristiano M., Stefano Bifaretti, Emilio Carfagna, Alessandro Lidozzi, Luca Solero, Fabio Crescimbini, and Marco Di Benedetto. "Speed Sensor Fault Tolerant PMSM Machines: From Position-Sensorless to Sensorless Control." IEEE Transactions on Industry Applications 55, no. 4 (July 2019): 3946–54. http://dx.doi.org/10.1109/tia.2019.2908337.

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25

Caileanu, C. "Sensorless Control Of AC Drives: Speed And Position Sensorless Operation [Book Review]." IEEE Industry Applications Magazine 3, no. 6 (November 1997): 65. http://dx.doi.org/10.1109/mia.1997.628149.

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26

Singh, Sachin, and Sanjeev Singh. "Position Sensorless Control for PMBLDC Motor Drive Using Digital Signal Processor." Journal of Circuits, Systems and Computers 25, no. 07 (April 22, 2016): 1650077. http://dx.doi.org/10.1142/s0218126616500778.

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This paper presents a complete position sensorless control scheme for permanent magnet brushless DC motors (PMBLDCMs) using back-EMF sensing method. The controller is designed in such a way that it provides smooth shifting from open-loop speed-up mode to back-EMF sensing mode at any speed, especially at very low speeds, i.e., less than 2% of the rated speed. The proposed scheme is a simple and cost effective implementation of back-EMF sensing method, which does not require any filtering or phase shift to generate commutation pulses. The proposed controller is designed and modeled for a PMBLDCM rated at 4600[Formula: see text]rpm, 310[Formula: see text]V and 2.2[Formula: see text]N[Formula: see text]m torque and its performance is simulated in MATLAB/SIMULINK environment. The obtained simulation results are validated on a prototype developed in the lab using a digital signal processor (DSP) namely TI 2812 DSP in a wide range of speeds in position sensorless mode.

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27

Sivakami, R., and Thangaraj K. "Speed control of sensorless brushless DC motor by computing back EMF from line voltage difference." International Journal of Advances in Applied Sciences 9, no. 2 (June 1, 2020): 125. http://dx.doi.org/10.11591/ijaas.v9.i2.pp125-131.

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Sensorless operation of permanent magnet brushless direct current (BLDC) motor drive controls the rotating speed with different applied voltage. No phase lagging is produced which leads to increase the efficiency and minimize the torque pulsation of the BLDC motor. Initially, motor can be started by following the v/f method then allows the sensorless mode after reaching the minimum speed of 500-1000rpm. The Sensorless BLDC motors are highly used due to higher efficiency, reliability power, acoustic noise, smaller, lighter, greater dynamic response, better speed versus torque characteristics, higher speed range and longer life. Thus the source voltage spikes and switching losses are reduced. This method can be demonstrated through MATLAB simulation and DSP TMS 320LF2407A is used in the experimental setup to get the output

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28

Peresada, S., Y. Nikonenko, V. Pyzhov, and D. Rodkin. "SENSORLESS SPEED CONTROL OF THE DIRECT CURRENT MOTORS." Praci Institutu elektrodinamiki Nacionalanoi akademii nauk Ukraini 2021, no. 58 (May 19, 2021): 23–29. http://dx.doi.org/10.15407/publishing2021.58.023.

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In this paper, a new speed control algorithm for a permanent magnet DC motor which does not require implementation of the angular speed sensor is presented. Three steps are performed to develop the control system: design of speed tracking control algorithm assuming the speed measurement; design of speed observer; design of sensorless speed control algorithm based on the principle of separation. Information about speed is taken from the speed observer using the motor current value. The stability of the composite system dynamics consisting of three subsystems (the speed regulation loop, current regulation loop, and speed observer) is analyzed. The feedback gains tuning procedure for decoupling of three subsystems is given. The simulation results show that the dynamic performance of the designed system is similar to the performance of the system with angular speed measurement. The resulting closed-loop system has structural robustness properties with respect to parametric and coordinate disturbances. References 12, figures 2.

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29

Liao, Zili, Qijin Zhao, Xinxi Zhang, and Luming Chen. "Research on Speed Sensorless Vector Control System of Asynchronous Motor Based on MRAS." MATEC Web of Conferences 160 (2018): 02006. http://dx.doi.org/10.1051/matecconf/201816002006.

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This paper analysed the basic principle of speed sensorless vector control system. Based on speed and current closed loop vector control, combined with a simple and feasible current hysteresis control strategy, the whole speed sensorless system of asynchronous motor is simulated in MATLAB/Simulink. The method uses the Model Reference Adaptive System (MRAS). The observation and analysis of waveform shows that the system has good static performance and robustness. The control effects are also as similar as the vector control system which contains speed sensor.

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Białoń, Tadeusz, Roman Niestrój, Jarosław Michalak, and Marian Pasko. "Induction Motor PI Observer with Reduced-Order Integrating Unit." Energies 14, no. 16 (August 11, 2021): 4906. http://dx.doi.org/10.3390/en14164906.

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This article presents an innovative induction motor state observer designed to reconstruct magnetic fluxes and the angular speed of an induction motor for speed sensorless control system applications such as field-oriented control (FOC). This observer is an intermediate solution between the proportional observer and the classical proportional-integral (PI) observer with respect to which the order of the integrating unit is reduced. Additional modifications of the observer’s structure have been implemented to ensure stability and to improve its functional properties. As a result, two versions of the observer structure were produced and experimentally tested using a sensorless FOC control system. Both structures resulted in correct control system operation for a wide range of angular speeds, including low speed ranges.

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31

Urbanski, Konrad, and Dariusz Janiszewski. "Sensorless Control of the Permanent Magnet Synchronous Motor." Sensors 19, no. 16 (August 14, 2019): 3546. http://dx.doi.org/10.3390/s19163546.

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This paper describes the study and experimental verification of sensorless control of permanent magnet synchronous motors with a high precision drive using two novel estimation methods. All the studies of the modified Luenberger observer, reference model, and unscented Kalman filter are presented with algorithm details. The main part determines trials with a full range of reference speeds with a special near-zero speed area taken into account. In order to compare the estimation performances of the observers, both are designed for the same motor and control system and run in the same environment. The experimental results indicate that the presented methods are capable of tracking the actual values of speed and motor position with small deviation, sufficient for precise control.

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32

Meng, Zhao Jun, Rui Chen, and Yue Jun An. "Direct Torque Control of Interior Permanent Magnet Synchronous Motors Based on Position Sensorless Control." Advanced Materials Research 756-759 (September 2013): 627–31. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.627.

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The position sensorless control method based on direct torque control was carried out aiming at the interior permanent magnet synchronous motor (IPMSM) in this paper. To the consideration of electric vehicle space is limited, in order to reduce the controller size to save space, this paper studied the sensorless control. Meanwhile, in order to improve the control rapidity as much as possible of the electric vehicle, take direct torque control as a control method of the driving motor. Finally, designed the sensorless direct torque controller and studied its simulation. Simulation results show that the control system have good dynamic and static characteristics in the full speed range.

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33

Horng, Jenq-Ruey, Ming-Shyan Wang, Tai-Rung Lai, and Sergiu Berinde. "A neural observer for sensorless speed control of servomotors." Engineering Computations 31, no. 8 (October 28, 2014): 1668–78. http://dx.doi.org/10.1108/ec-11-2012-0289.

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Purpose – Extensive efforts have been conducted on the elimination of position sensors in servomotor control. The purpose of this paper is to aim at estimating the servomotor speed without using position sensors and the knowledge of its parameters by artificial neural networks (ANNs). Design/methodology/approach – A neural speed observer based on the Elman neural network (NN) structure takes only motor voltages and currents as inputs. Findings – After offline NNs training, the observer is incorporated into a DSP-based drive and sensorless control is achieved. Research limitations/implications – Future work will consider to reduce the computation time for NNs training and to adaptively tune parameters on line. Practical implications – The experimental results of the proposed method are presented to show the effectiveness. Originality/value – This paper achieves sensorless servomotor control by ANNs which are seldom studied.

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34

Urbanski, Konrad. "Sensorless control of PMSM for low speed range." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 34, no. 3 (May 5, 2015): 754–65. http://dx.doi.org/10.1108/compel-10-2014-0275.

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35

Altaey, Abdulhasan, and Ahmet Afsin Kulaksiz. "Stability analysis of sensorless speed control of IPMSM." IEEJ Transactions on Electrical and Electronic Engineering 12 (December 2017): S101—S112. http://dx.doi.org/10.1002/tee.22569.

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Urbański, Konrad. "Sensorless control of SRM at medium speed range." Archives of Electrical Engineering 60, no. 2 (June 1, 2011): 179–85. http://dx.doi.org/10.2478/v10171-011-0017-4.

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Sensorless control of SRM at medium speed rangeThe paper deals with the problem of position and speed estimation methods in SRM (Switched Reluctance Motor) drive equipped with hysteresis band current controller with MRAS (Model Reference Adaptive System) type observer. An adaptive flux model uses equation set of one-dimensional equations instead of one two-dimensional equation. The reference model is the formal one. Instead of measured current the observer utilizes reference current. Such drive system works well at speed range up to 600 rad/s. The observer's gains must change depend on the speed range. The robustness on motor parameter poor estimation is presented.

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Rong-Jong Wai. "Hybrid control for speed sensorless induction motor drive." IEEE Transactions on Fuzzy Systems 9, no. 1 (February 2001): 116–38. http://dx.doi.org/10.1109/91.917119.

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Wang, Hong Yu, Yan Peng, and Yan Hou. "Design and Simulation of Speed Sensorless Control System for Induction Motor." Applied Mechanics and Materials 201-202 (October 2012): 396–99. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.396.

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In this paper, a method for estimating induction motor’s rotor speed is proposed. The proposed rotor speed estimation method is based on model reference adaptive identification theory. By applying the proposed method, the induction motor control system can estimate the rotor speed of the induction motor precisely. To improve the rotor speed estimation performance of the system, one input filter and one output filter are introduced into the speed sensorless control system. The introduced input filter and output filter enhance the estimation accuracy and improve the reliability and robustness of the system. The speed sensorless control system based on proposed method was built with Simulink blocks in Matlab platform. The simulation results indicate that the proposed method can operate stably in whole range of speed with preferable identification precision of the rotor speed.

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Li, Yong, Hao Wu, Xing Xu, Xiaodong Sun, and Jindong Zhao. "Rotor Position Estimation Approaches for Sensorless Control of Permanent Magnet Traction Motor in Electric Vehicles: A Review." World Electric Vehicle Journal 12, no. 1 (January 10, 2021): 9. http://dx.doi.org/10.3390/wevj12010009.

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Permanent magnet traction motor has the advantages of high efficiency, high power density, high torque density and quick dynamic response, which has been widely used in the traction field of electric vehicle. The high-performance control of permanent magnet traction motor depends on accurate rotor position information, which is usually obtained by using mechanical position sensors such as hall sensor, encoder and rotary transformer. However, the traditional mechanical sensor has the disadvantages of high cost, large volume and poor anti-interference ability, which limits the application of permanent magnet motor. The sensorless control technology is an effective way to solve the above-mentioned problem. Firstly, the sensorless control techniques of permanent magnet motor are classified. The sensorless control techniques of permanent magnet motor for rotor initial position, zero-low speed range, medium-high speed range and full speed range are deeply described and compared. Finally, the development trend of sensorless control technology of permanent magnet traction motor is prospected.

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Li, Yong, Hao Wu, Xing Xu, Xiaodong Sun, and Jindong Zhao. "Rotor Position Estimation Approaches for Sensorless Control of Permanent Magnet Traction Motor in Electric Vehicles: A Review." World Electric Vehicle Journal 12, no. 1 (January 10, 2021): 9. http://dx.doi.org/10.3390/wevj12010009.

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Permanent magnet traction motor has the advantages of high efficiency, high power density, high torque density and quick dynamic response, which has been widely used in the traction field of electric vehicle. The high-performance control of permanent magnet traction motor depends on accurate rotor position information, which is usually obtained by using mechanical position sensors such as hall sensor, encoder and rotary transformer. However, the traditional mechanical sensor has the disadvantages of high cost, large volume and poor anti-interference ability, which limits the application of permanent magnet motor. The sensorless control technology is an effective way to solve the above-mentioned problem. Firstly, the sensorless control techniques of permanent magnet motor are classified. The sensorless control techniques of permanent magnet motor for rotor initial position, zero-low speed range, medium-high speed range and full speed range are deeply described and compared. Finally, the development trend of sensorless control technology of permanent magnet traction motor is prospected.

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Niasar, Abolfazl Halvaei, Hossein Rahimi Khoei, Mahdi Zolfaghari, and Hassan Moghbeli. "Artificial Neural Network Based Sensorless Vector Control of Induction Motor Drive." Applied Mechanics and Materials 704 (December 2014): 325–28. http://dx.doi.org/10.4028/www.scientific.net/amm.704.325.

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Controlled induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. For these speed sensorless AC drive system, it is key to realize speed estimation accurately. This paper describes a Model Reference Adaptive System (MRAS) based scheme using Artificial Neural Network (ANN) for online speed estimation of sensorless vector controlled induction motor drive. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab. Simulation result shows a good performance of speed estimator. Also Performance analysis of speed estimator with the change in resistances of stator is presented. Simulation results show this estimator robust to resistances of stator variations.

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Son, Ju-Beom, Hong-Ryel Kim, Young-Soo Seo, and Jang-Myung Lee. "PMSM Sensorless Speed Control Using a High Speed Sliding Mode Observer." Journal of Institute of Control, Robotics and Systems 16, no. 3 (March 1, 2010): 256–63. http://dx.doi.org/10.5302/j.icros.2010.16.3.256.

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Fang-Zheng Peng and T. Fukao. "Robust speed identification for speed-sensorless vector control of induction motors." IEEE Transactions on Industry Applications 30, no. 5 (1994): 1234–40. http://dx.doi.org/10.1109/28.315234.

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Singh, Shweta, Amar N. Tiwari, and Sri N. Singh. "Sensor-based and Sensorless Vector Control of Permanent Magnet Synchronous Motor Drives: A Comparative Study." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 2 (April 27, 2020): 276–84. http://dx.doi.org/10.2174/2352096511666180724104302.

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Background: Speed and rotor position estimation is mandatory for vector control scheme of Permanent Magnet Synchronous Motor (PMSM). Methods: The estimation accuracy of Non-adaptive (Open loop) methods degrades as mechanical speed reduces. The system becomes more robust against parameter mismatch and signal noises by employing adaptive observers for estimation of speed and position. Sensorless scheme adopted for estimating the PMSM rotor position based on its performance which eliminates the need for speed sensors which are usually required in such control applications. Results: To achieve this goal, a Space Vector Pulse Width Modulation (SVPWM) control scheme is applied to work in conjunction with a vector control PMSM drive using Simulink. The PI controller uses from estimated speed feedback for the speed sensorless control of PMSM. Conclusion: In this paper, a comprehensive analysis of sensor-based and sensorless based on Sliding Mode Observer (SMO) techniques for vector control of PMSM is presented with regards to the steadystate and dynamic performance robustness against parameter sensitivity, stability and computational complexity. The control scheme is simulated in the MATLAB/Simulink software environment.

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Hua, Yizhou, and Huangqiu Zhu. "Sensorless Control of Bearingless Permanent Magnet Synchronous Motor Based on LS-SVM Inverse System." Electronics 10, no. 3 (January 23, 2021): 265. http://dx.doi.org/10.3390/electronics10030265.

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In order to solve the problems of low integration, low reliability, and high cost caused by mechanical sensors used in bearingless permanent magnet synchronous motor (BPMSM) control systems, a novel speed and displacement sensorless control method using a least-squares support vector machine (LS-SVM) left inverse system is proposed in this paper. Firstly, the suspension force generation principle of the BPMSM is introduced, and the mathematical model of the BPMSM is derived. Secondly, the observation principle of the left inverse system is explained, and the left reversibility of the established speed and displacement subsystem is proved. Thirdly, the left inverse systems of the speed and displacement subsystems are constructed by using the LS-SVM, and the complete speed and displacement sensorless control system is constructed. Finally, the simulations and experiments of the proposed method are performed. The research results demonstrate that the proposed observation method can identify the speed and displacement quickly and accurately, and the sensorless control method can realize the stable operation of the BPMSM without speed and displacement sensors.

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Dumnic, Boris, Dragan Milicevic, Bane Popadic, Vladimir Katic, and Zoltan Corba. "Speed-sensorless control strategy for multi-phase induction generator in wind energy conversion systems." Thermal Science 20, suppl. 2 (2016): 481–93. http://dx.doi.org/10.2298/tsci151019032d.

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Renewable energy sources, especially wind energy conversion systems (WECS), exhibit constant growth. Increase in power and installed capacity led to advances in WECS topologies. Multi-phase approach presents a new development direction, with several key advantages over three-phase systems. Paired with a sensorless control strategy, multi-phase machines are expected to take primacy over standard solutions. This paper presents speed sensorless vector control of an asymmetrical six-phase induction generator based on a model reference adaptive system (MRAS). Suggested topology and developed control algorithm show that sensorless control can yield appropriate dynamic characteristics for the use in WECS with increase in reliability and robustness.

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Lu, Hua Cai, Xuan Yu Yao, and Juan Ti. "Combined Back-EMF Estimator with High-Frequency Signal Injection for Wide Speed Range Sensorless Control of PMLSM." Advanced Materials Research 753-755 (August 2013): 1405–8. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1405.

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This paper describes a composite sensorless position and speed detection algorithm designed for permanent magnet linear synchronous motor (PMLSM). A high-frequency voltage signal injection method is used at starting and low speed, and a back-EMF integrate method is used at high speed, and the two kinds of method are fused by weighting method in the transition speed area. Simulation results show that estimation accuracy of this composite estimation method is satisfactory, and the sensorless control system based on this method has good dynamic response characteristics within full speed.

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Halvaei Niasar, Abolfazl, Marzieh Ahmadi, and Sayyed Hossein Edjtahed. "Sensorless Control of Nonsinusoidal Permanent Magnet Brushless Motor Using Selective Torque Harmonic Elimination Control Method Based on Full-Order Sliding Mode Observer." Advances in Power Electronics 2016 (December 8, 2016): 1–13. http://dx.doi.org/10.1155/2016/9358604.

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Nowadays, due to excellent advantages of permanent magnet brushless (PMBL) motors such as high efficiency and high torque/power density, they are used in many industrial and variable-speed electrical drives applications. If the fabricated PMBL motor has neither ideal sinusoidal nor ideal trapezoidal back-EMF voltages, it is named nonideal (or nonsinusoidal) PMBL motor. Employing conventional control strategies of PMSMs and BLDCMs lowers the efficiency and leads to unwanted torque ripple, vibration, and acoustic noises. Moreover, in many applications to reduce the cost and enhance the reliability of drive, sensorless control techniques are used. This paper proposes a novel sensorless control for a nonsinusoidal PMBL motor with minimum torque ripple. To develop smooth torque, the selected torque harmonic elimination strategy is employed. Furthermore, to estimate the rotor position and speed, a novel full-order sliding mode observer is designed. Proposed observer estimates the position and speed of motor from standstill to final speed. The proposed observer is robust to uncertainty of harmonic contents in phase back-EMF voltage and able to run the motor from standstill with closed-loop control scheme. The capabilities of torque ripple minimization and sensorless strategies are demonstrated with some simulations.

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Saadaoui, Oussama, Amor Khlaief, Moez Abassi, Abdelkader Chaari, and Mohamed Boussak. "A rotor initial position estimation method for sensorless field-oriented control of permanent magnet synchronous motor." Transactions of the Institute of Measurement and Control 40, no. 15 (January 24, 2018): 4198–207. http://dx.doi.org/10.1177/0142331217744848.

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In this paper, a new technique to improve initial rotor position detection at standstill of a permanent magnet synchronous motor (PMSM) is presented. Sensorless field-oriented control (FOC) of a PMSM at low speed remains a difficult task. In order to estimate the position and rotor speed, we proposed a novel structure of a full-order sliding mode observer (FO-SMO) in a sensorless FOC. At standstill, we used a voltage pulse sequence applied to the windings in order to detect the initial rotor position. With this technique, we managed to minimize the error on the estimated rotor position to 3.75° (electrical) compared with others. The validity of the proposed approach with a 1.1-kW low-speed PMSM sensorless FOC has been proved by experimental results.

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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.

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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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