Relevant bibliographies by topics / Sensorless speed control and adaptive observation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Sensorless speed control and adaptive observation'

Author: Grafiati
Published: 7 June 2025
Last updated: 17 July 2025

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Journal articles on the topic "Sensorless speed control and adaptive observation"

1

Pei, Zifeng, Li Zhang, Haijun Fu, and Yucheng Wang. "New Fault-Tolerant Sensorless Control of FPFTPM Motor Based on Hybrid Adaptive Robust Observation for Electric Agricultural Equipment Applications." Energies 18, no. 8 (2025): 1962. https://doi.org/10.3390/en18081962.

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This paper proposes a hybrid adaptive robust observation (HARO)-based sensorless control strategy of a five-phase fault-tolerant permanent-magnet (FPFTPM) motor for electric agricultural equipment applications under various operating conditions, including fault conditions. Regarding fault-tolerant sensorless control, the existing studies usually treat fault-tolerant control and sensorless control as two independent units rather than a unified system, which makes the algorithm complex. In addition, under the traditional fault-tolerant algorithm, the system needs to switch after diagnosis when the fault occurs, which leads to a degraded sensorless control performance. Hence, this paper proposes a fault-tolerant sensorless control strategy that can achieve the whole speed range without fault-tolerant switching. At zero/low speed, a disturbance adaptive controller (DAC) architecture is developed by treating phase faults as system disturbances, where robust controllers and extended state observer (ESO) collaboratively suppress speed and position errors. At medium/high speeds, this paper provides a steady-healthy SMO, which combines the enhanced observer and universal phase-locked loop (PLL) without phase compensation. With above designs, the proposed strategy can significantly improve the estimated accuracy of rotor position under normal conditions and fault circumstances, while simplifying the complexity of the fault-tolerant sensorless algorithm. Furthermore, the proposed strategy is verified based on the experimental platform of the FPFTPM motor drive system. The experimental results show that compared with the traditional method, the torque ripple and position error are reduced by nearly 20% and 60%, respectively, at zero-low speed and medium-high speed, and the torque ripple is reduced by 55% during fault operation, which verifies the robustness and effectiveness of the proposed method.
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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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VIT. "Sliding Mode Without Sensors Induction Motor Drive Vector Control." Journal of Engineering Technology and Sciences 02, no. 03 (2025): 17–21. https://doi.org/10.5281/zenodo.14998091.

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<em>This research discusses the design process of sliding mode controllers used for sensorless field-oriented induction motor control. A sliding mode regulator uses a sliding surface integration for speed regulation to improve controller performance. The adaptive observer implements the MRAS technique which determines rotor speed estimation used in the speed feedback loop. The experimental research verifies the effectiveness of this proposed method.</em>
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Hu, Hailin, Shiyan Yu, Liangjie Ren, Mingda Zhai, and Yuhui Chen. "Improved Interconnected MRAS Parameter Identification for Speed Sensorless Control of Linear Induction Motor." Actuators 14, no. 1 (2024): 2. https://doi.org/10.3390/act14010002.

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After eliminating the speed sensor in the linear induction motor (LIM) high-performance closed-loop control system, the speed feedback information is missing in the speed closed loop. The accuracy of speed observation results is affected by changes in magnetizing inductance and primary resistance. This effect can cause significant oscillations in the results of the speed sensorless control system, preventing them from converging. An enhanced model reference adaptive system (MRAS) multi-parameter parallel identification methodology based on the interconnected second-order super-twisting algorithm (SOSTA) is proposed. To enhance the system’s dynamic performance, we designed an improvement to the MRAS observer based on the SOSTA, with a focus on the LIM state-space equation that considers dynamic edge-end effects. The impact of parameter alterations on the LIM system is examined. To improve speed observation accuracy and system stability, a two-parameter MRAS identification model was created. The Popov hyperstability principle was used to formulate control laws for these two parameters, ultimately enabling the identification of these two parameters. The identified values were fed back to the speed observation and control system, which reduces the coupling of these two parameters and speed. Simulation and hardware-in-the-loop experiments demonstrate that the observation system estimates speed accurately when these two parameters undergo abrupt changes within the rated speed range, enhancing the precision and robustness of the speed sensorless control system.
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Cao, Yang, and Jian Guo. "Sensorless Control of High-Speed Motors Subject to Iron Loss." Energies 15, no. 20 (2022): 7615. http://dx.doi.org/10.3390/en15207615.

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It is widely recognized that the iron loss produced by motors at high speeds will directly affect the angle and size of the back electromotive force, and, therefore, it cannot be ignored. In this paper, a high-performance sensorless control algorithm is proposed for high-speed permanent magnet synchronous motors (HSPMSM), taking the iron loss into account. First, the resistance representing the core loss is precalculated by finite element analysis, and then a sliding mode observer with disturbance observation is designed to estimate the rotor position. The observer possesses the advantages of suppressing the chattering phenomenon and enhancing the robustness against uncertainty. Meanwhile, the idea of the characteristic model is used to design an adaptive robust control law to improve the speed control accuracy. Subsequently, a sensorless control scheme is proposed by using the proposed observer in combination with the designed control scheme. The stability of the observer and controller is verified by the Lyapunov theory method. Finally, a simulation example is given to demonstrate the correctness and the effectiveness of the proposed algorithm.
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Stando, Dariusz, and Marian P. Kazmierkowski. "Simple Technique of Initial Speed Identification for Speed-Sensorless Predictive Controlled Induction Motor Drive." Power Electronics and Drives 5, no. 1 (2020): 189–98. http://dx.doi.org/10.2478/pead-2020-0014.

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Abstract This article presents a simple technique of identifying the initial speed that allows for restarting a sensorless induction motor (IM) drive controlled by a model predictive flux control (MPFC). Initial speed identification is required because, according to the research, the applied current-model reference adaptive system (C-MRAS) can restart the IM after failure only if the error of the initial speed set in the estimator is &lt;25%. The proposed technique is based on short periods of flux generation for the certain initial speed and observation of the estimated torque respond. The direction of the estimated torque determines whether the real speed is higher or lower than the initial one set in the estimator. In two steps, the algorithm identifies the initial speed with an accuracy of 25%. This allows for a quick restart of the IM from any speed, eliminating the disadvantage of the sensorless drive control system with the C-MRAS speed estimator. The experimental results measured on a 50 kW drive which illustrates the operation and performances of the system are presented.
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Liu, Yubo, Junlong Fang, Kezhu Tan, Boyan Huang, and Wenshuai He. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM." Energies 13, no. 22 (2020): 5991. http://dx.doi.org/10.3390/en13225991.

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To improve the observation accuracy and robustness of the sensorless control of an interior permanent magnet synchronous motor (IPMSM), a sliding mode observer based on the super twisting algorithm (STA-SMO) with adaptive parameters estimation control is proposed, as parameter mismatches are considered. First, the conventional sliding mode observer (CSMO) is analyzed. The conventional exponential approach law produces a large chattering phenomenon in the back EMF estimation, which causes a large observation error when filtering the chattering through the low-pass filter. Second, a high-order approach law of the super twisting algorithm is introduced to observe the rotor position and speed estimation, which uses the integral function to eliminate the chattering of the sliding mode. Third, an adaptive parameter estimation control (APEC) is presented to enhance the observation accuracy caused by parameter mismatches; the motor parameter adaptive law of the APEC is designed by Lyapunov’s stability law. Finally, the proposed method not only reduces both the chattering and the low-pass filter, but it also enhances accuracy and robustness against parameter mismatches, as discussed through simulations and experiments.
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Fan, Bo, Zhi-Xin Yang, Xian-Bo Wang, Lu Song, and Shu-Zhong Song. "Model reference adaptive vector control for induction motor without speed sensor." Advances in Mechanical Engineering 9, no. 1 (2017): 168781401668308. http://dx.doi.org/10.1177/1687814016683086.

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The wide applications of vector control improve the high-accuracy performance of alternating current (AC) adjustable speed system. In order to obverse the full-order flux and calculate the real-time speed, this article introduces the motor T equivalent circuit to build a full-order flux observer model, where the current and flux variables of stator and rotor are adopted. Model reference adaptive control is introduced to build the AC motor flux observer. The current output is used as feedback to build the feedback matrix. The calculation method of motor speed, which is part of the inputs of flux observation, is applied to realize the adaptive control. The concept of characteristic function is introduced to calculate the flux, of which the foundation is the variables of composite form of voltage and current models. The characteristic function is deduced as a relative-state variable function. The feedback matrix is improved and designed to ensure the motor flux observer is a smooth switch between current and voltage model in low and high speeds, respectively. Experimental results show that the feedback and characteristic model are feasible, and the vector control with speed sensorless based on the full-order flux observer has better performance and anti-disturbance.
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Luan, Mingchen, Jiuhong Ruan, Yun Zhang, Haitao Yan, and Long Wang. "An Improved Adaptive Finite-Time Super-Twisting Sliding Mode Observer for the Sensorless Control of Permanent Magnet Synchronous Motors." Actuators 13, no. 10 (2024): 395. http://dx.doi.org/10.3390/act13100395.

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In order to improve the observation accuracy of rotor positions in the sensorless control of permanent magnet synchronous motors and to simplify the parameter adjustment process, this paper proposes an improved finite-time adaptive super-twisting sliding mode observer. First, a linear gain term is introduced into the conventional super-twisting sliding mode observer model as a way of improving the identification accuracy of the observer. Then, for the multi-parameter variable problem in the traditional observer model, a rotational speed variable function design is presented, which simplifies the multi-variables into a single adaptive variable. This reduces the complexity of the observer model while further improving the observation accuracy and stability of the improved observer algorithm (which is verified using Lyapunov’s stability theory). A new back EMF filter and an adaptive phase-locked loop are then used to improve the model’s speed tracking capability. Finally, through simulation and experimental tests, the improved algorithm’s ability to quickly observe changes in rotor position and speed, as well as its fast convergence, small jitter and high accuracy characteristics, are verified.
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Chen, Huipeng, Zhiqiang Yao, Yongqing Liu, et al. "PMSM Adaptive Sliding Mode Controller Based on Improved Linear Dead Time Compensation." Actuators 11, no. 9 (2022): 267. http://dx.doi.org/10.3390/act11090267.

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Aiming at the issue of the sliding mode observer (SMO) being sensitive to the motor model parameters at low speeds, a rotor position observation method based on resistance adaptive SMO and considering the influence of inverter dead time is designed in this paper. In this method, the online resistance identification is introduced into the conventional SMO, the resistance parameters of the SMO are modified in real-time, and the online resistance identification algorithm is designed by using the Lyapunov function. An enhanced linear dead time compensation method is proposed to improve the resistance adaptive SMO and eliminate the voltage error between the estimated and the actual motor models in order to address the impact of inverter dead time on the voltage parameters in the estimation model at low speeds. Simulation results show that the online resistance identification and dead time compensation can significantly improve the accuracy of sensorless speed control at low speeds, and the dead time compensation can also improve the accuracy of online resistance identification.
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Dissertations / Theses on the topic "Sensorless speed control and adaptive observation"

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Sevinc, Ata. "Speed sensorless control of induction motors." Thesis, University of Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364962.

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Li, Jingchuan. "Adaptive sliding mode observer and loss minimization for sensorless field orientation control of induction machine." Columbus, Ohio : Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1132428071.

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Simsek, Gunay. "Sensorless Direct Field Oriented Control Of Induction Machine By Flux And Speed Estimation Using Model Reference Adaptive System." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12604965/index.pdf.

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ABSTRACT SENSORLESS DIRECT FIELD ORIENTED CONTROL OF INDUCTION MACHINE BY FLUX AND SPEED ESTIMATORS USING MODEL REFERENCE ADAPTIVE SYSTEM This work focuses on an observer design which will estimate flux-linkage and speed for induction motors in its entire speed control range. The theoretical base of the algorithm is explained in detail and its both open-loop, and closed-loop performance is tested with experiments, measuring only stator current and voltage. Theoretically, the field-oriented control for the induction motor drive can be mainly categorized into two types<br>indirect and direct field oriented. The field to be oriented may be rotor, stator, or airgap flux-linkage. In the indirect field-oriented control, the slip estimation based on the measured or estimated rotor speed is required in order to compute the synchronous speed. There is no need for the flux estimation in such a system. For the direct field oriented case the synchronous speed is computed with the aid of a flux estimator. In DFO, the synchronous speed is iv computed from the ratio of dq-axes fluxes. With the combination of a flux estimator and an open-loop speed estimator one can observe stator-rotor fluxes, rotor-flux angle and rotor speed. In this study, the direct (rotor) flux oriented control system with flux and-open-loop speed estimators is described and tested in real-time with the Evaluation Module named TMS320LF21407 and the Embedded Target software named Vissim from Visual Solutions Company.
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Goksu, Omer. "Shaft Transducerless Vector Control Of The Interior Permanent Magnet Motor With Speed And Position Estimation Using High Frequency Signal Injection And Flux Observer Methods." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609617/index.pdf.

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In this thesis, shaft transducerless vector control of Interior Permanent Magnet (IPM) motor with speed and position estimation using saliency based high frequency signal injection and fundamental model based flux observer methods will be investigated. The magnetic saliency characteristic of a 2.2-kW IPM motor will be experimentally extracted by means of high frequency signal injection. High frequency signal injection method will be used to estimate the speed and position at zero and low speed based on the magnetic saliency of the IPM motor. At high speed, fundamental model based flux observer method will be utilized for speed and position estimation. Seamless transition between the two estimation methods will be provided. Using the estimated speed and position information, the motor will be closed loop vector controlled and the drive motion performance over wide speed and load range will be investigated. The IPM motor drive and the estimation/control algorithms will be modeled and their performance will be demonstrated by detailed computer simulations. A three-phase voltage source inverter and a motor test bench will be built, and the estimation/control algorithms will be implemented on a DSP based motor control platform. The IPM motor drive system will be tested in the laboratory and the theory and simulation results will be verified by the experiments.
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Agrebi, Zorgani Youssef. "Estimation adaptative de la vitesse et de la résistance rotorique pour la commande par orientation du flux statorique d’un moteur asynchrone sans capteur mécanique." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM4360.

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Les travaux de recherche développés, dans ce rapport de thèse de Doctorat traitent la commande vectorielle indirecte par orientation du flux statorique d'une machine asynchrone avec ou sans capteur de vitesse. L'approche développée utilise la méthode adaptative avec modèle de référence. Le modèle de référence ainsi que le modèle ajustable, qui sont développés dans un repère lié au stator, sont utilisés pour l'estimation de la vitesse de rotation, de la résistance rotorique et enfin l'estimation mutuelle de la vitesse de rotation et de résistance rotorique d'une machine asynchrone à partir de la connaissance des courants et tensions statoriques. Pour annuler l'erreur statique lors de la régulation de la vitesse et améliorer par la suite les performances des résultats obtenus, le couple résistant, qui peut être considéré comme une perturbation, a été estimé en se basant sur les variables d'état du moteur à commander. Pour cela une procédure d'estimation du couple résistant de la même machine a été développée en se basant sur un observateur de type Luenberger. Les résultats de simulation numérique obtenus dans l'environnement Matlab- Simulink ainsi que les résultats expérimentaux, obtenus sur deux plates formes d'essais de machines asynchrones équipées chacune d'une carte de commande temps réel de type DS1104, valident bien les algorithmes développés<br>The research developed in this PhD report deal with indirect stator field oriented control (ISFOC) of an induction motor drive (IM), with and without speed sensor. The developed approach uses the method with Model Reference Adaptive System (MRAS). The reference model and the adjustable one, which are developed in stationary stator reference frame, are used to estimate the rotor speed, the rotor resistance and the simultaneous estimation of speed and rotor resistance of the (IM) from the knowledge of the stator currents and voltages. To cancel the static error in the speed control and ameliorate subsequently the performance results, the load torque, which can be considered as a disturbance, has been estimated based on the state variables of the motor to be controlled. For this, a procedure was developed to estimate the torque of the same machine based on a Luenberger observer. The numerical simulations results obtained with Matlab-Simulink software package as well as the experimental results, obtained on two platforms for testing asynchronous machines each equipped with a real time controller board of dSPACE, validate the developed algorithms
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Chang, Ren-Jye, and 張仁杰. "Nonlinear adaptive sensorless speed control for induction motors considering rotor resistance variation." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/96270017087503668651.

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碩士<br>國立臺灣大學<br>電機工程學系<br>85<br>In this thesis, a nonlinear adaptive sensorless speed controller for inductionmotors is proposed. In the controller, only the stator currents are assumed tobe measurable. Flux observers and rotor speed estimator are designed to relaxthe need of flux and speed measurement. Besides, an estimator is also designedto overcome drifting problem of the rotor resistance. Rigorous stability analysisbased on Lyapunov theory is also performed to guarantee that the controllerdesigned here is stable. Computer simulations and experiments are done to demonstrate the performance of our design.
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HUANG, HSIN-SAIN, and 黃心聖. "Nonlinear Sensorless Indirect Adaptive Speed Control of Induction Motor with Maximum Power Transfer." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/16954980324386345495.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>88<br>In this thesis, we will derive the maximum power transfer theorem at first. Then, a nonlinear indirect adaptive sensorless speed tracking controller for induction motor subjects to the maximum power transfer is proposed. In this controller, only the stator currents are assumed to be measurable. The rotor flux and speed observers are designed to relax the need of flux and speed measurement. Besides, the rotor resistance estimator is also designed to cope with the shifting problem of the rotor resistance. Stability analysis based on Lyapunov theory is also performed to guarantee that the controller design here is stable. Also, the computer simulations and experiments are done to demonstrate the performance of our design and maximum power transfer.
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Wang, Wei-Cheng, and 王威程. "Sliding Mode Based Adaptive Flux Observer for Sensorless Speed Vector Control of Induction Motor Drives." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/a658ny.

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碩士<br>崑山科技大學<br>電機工程研究所<br>97<br>Sliding mode scheme based current controller and rotor flux observer are proposed in this thesis for sensorless speed direct field-oriented control induction motor drives. The flux observers used in direct field-oriented control are often sensitive to the machine parameters. In this thesis, an adaptive sliding mode observer robust to parameters variations is adopted. The adopted adaptive sliding mode observer consists of two current observers and one rotor flux observer. The effects of parameter deviations on the rotor flux observer can be alleviated by the interaction of these two current sliding mode observers in this method. Speed estimation is derived from the stability theory based on the current and rotor flux observers. In this thesis, quadrature detector method is utilized to solve the pure integration problem on the rotor flux observer. This thesis combine the above adaptive sliding mode flux observer with the sliding mode current controller proposed in [19] and apply to a speed sensorless induction motor drivers. First, the proposed control scheme has simulated by MATLAB/Simulink toolbox software to verify the feasibility of the proposed strategy and constructed a PC-based experimental system to test the performances of the drive system. From the experimental results, the system still owns excellent robustness and tracking ability under parameters variations and load disturbances.
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Chen, Guan Zhou, and 陳冠州. "The study of speed sensorless vector control for induction motor with model reference adaptive system." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/48688219320517991275.

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碩士<br>中正理工學院<br>電機工程研究所<br>86<br>How to apply vector control technique to induction motor with model reference adaptive system(MRAS) is what we study in this paper. The first, the MRAS estimates rotor flux, electrical angular velocity, and rotor speed, instead of the sensor feedback in the tradition. So, in order to improve estimation accuracy we modify the original design. Next, design the speed controller with MRAS instead of the original PI controller. The MRAS speed controller have no setting parameter problem as PI controller, better speed response in low speed, and better ability with load. Simulation results are obtained by running the Pentium 200 personal computer(PC) with the software MATLAB* SIMULINK*. The experiment is taken by a 3 phase induction motor drive based on PC and an induction motor assembly set. The simulation results of MRAS estimator is not good with speed command 1800rpm of load and no load. However, there are improving speed accuracy after modifying MRAS estimator algorithm. Otherwise, the experiment is good with speed command 180rpm. The simulation results of speed controller designed with MRAS, have no setting parameter problem as PI controller, better speed response in low speed, and better ability with load. The average root mean square error(RMSE) is only 0.0449rpm in speed 1rpm specially. In the experiment results, proceed many kind speed commands to confirm that the MRAS speed controller is superior. So, results of simulation and experiment prove that the paper presents the application of MRAS to estimator and controller having good performance.
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Chin-Yu, Tsai, and 蔡錦煜. "Nonlinear Sensorless Indirect Adaptive Position and Speed Control of Induction Motor with Unknown Rotor Resistance." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/41881096632407579807.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>87<br>In this thesis, a nonlinear indirect adaptive sensorless speed/position tracking controller for induction motors is proposed. In the controller, only the stator currents are assumed to be measurable. The rotor flux, position and speed observer are designed to relax the need of flux and position measurement. Besides, the rotor resistance estimators are also designed to cope with the drifting problem. Rigorous stability analysis based on Lyapunov theory is also performed to guarantee that the controller designed here is stable. Also, the computer simulations and experiments are done to demonstrate the performance of our design.
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Book chapters on the topic "Sensorless speed control and adaptive observation"

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Quan, Longhu, Zhanshan Wang, Xiuchong Liu, and Mingguo Zheng. "Sensorless PMSM Speed Control Based on NN Adaptive Observer." In Advances in Neural Networks – ISNN 2014. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12436-0_12.

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Yin, Shaobo, Yuwen Qi, Yi Xue, Huaiqiang Zhang, and Dongyi Meng. "Optimized Discrete Model Based Model Reference Adaptive System for Speed Sensorless Control." In Lecture Notes in Electrical Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7986-3_20.

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El Mahfoud, Mohammed, Badre Bossoufi, Najib El Ouanjli, Said Mahfoud, Mourad Yessef, and Mohammed Taoussi. "Speed Sensorless Direct Torque Control of Doubly Fed Induction Motor Using Model Reference Adaptive System." In Digital Technologies and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73882-2_165.

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Liu, Lanjiao, Zefeng Huang, Zihe Liu, Liguo Tian, Ziming Liu, and Wenjie Xiao. "Study on Gain-Adaptive Super-Twisting Sliding Mode Observer for Sensorless Disturbance-Rejection Speed Control in High-Speed PMSM." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1395-3_13.

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Niasar, Abolfazl Halvaei, Hassan Moghbelli, and Mojtaba Yavari. "Sensorless Speed Control of Hystersis Motor Based on Model Reference Adaptive System and Luenberger Observer Techniques." In Neural Information Processing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34500-5_54.

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Zhang, Wenbai, Guobin Lin, Yuanzhe Zhao, Zhiming Liao, and Huan Wang. "Research on Sensorless Control Strategy of High-Speed Maglev Train Based on Extended Full-Order State Adaptive Observer." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-66971-2_21.

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Indriawati, Katherin, and Ricko Supriyanto. "Sensorless Speed Control of Induction Motor Drives Using Disturbance Observer and Adaptive PID Controller." In Advances in Transdisciplinary Engineering. IOS Press, 2024. https://doi.org/10.3233/atde241237.

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This study discusses the development of a sensorless speed control method for induction motors using an adaptive PID Controller. An approach is proposed that utilizes a disturbance observer to estimate the speed of the induction motor. Subsequently, an adaptive PID Controller is implemented to regulate speed control with real-time parameter adjustments based on the motor’s operating conditions. Experimental results show that the combination of these two methods enhances dynamic response performance, particularly in avoiding overshoot and steady-state error. By applying this technique, effective control is achieved without the need for additional sensor devices, leading to reduced costs and system complexity. This research makes an important contribution to the development of more efficient and reliable induction motor technology and opens avenues for further research in sensorless control applications.
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Agrebi Zorgani, Youssef, Soufien Hajji, Yessine Koubaa, and Mohamed Boussak. "Model Reference Adaptive System Scheme for Sensorless Induction Motor Drive." In Induction Motors - Recent Advances, New Perspectives and Applications [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.1001160.

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Indirect flux-oriented control (FOC) techniques are now widely used for the control of induction motor drives in highperformance applications. For the stator-flux-oriented control (SFOC) induction motor drive, the rotor position – using an incremental optical or magnetic encoder sensor placed on the shaft – and information of the current’s components are continuously required. However, the rotor position sensor leads to reduced reliability and requires additional cabling and space on the shaft. It also increases cost, weight and susceptibility to noise. To overcome these problems, the use of sensorless control without a mechanical sensor is an attractive solution. In previous works , the MRAS scheme has been used to estimate the speed and the rotor resistance. This control method is presented for the sensorless indirect stator-flux-oriented control (ISFOC) induction motor (IM) drive.
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Men, Qiang, Jiaming Cai, Junbi Tan, and Xiangtao Fang. "Rotor Position Estimation of Permanent Magnet Synchronous Motor Based on Disturbance Model." In Advances in Energy Research and Development. IOS Press, 2022. http://dx.doi.org/10.3233/aerd220035.

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Aiming at the high reliability of sensorless control of permanent magnet synchronous motor (PMSM), a back EMF estimator based on disturbance model is proposed. The back EMF in the assumed coordinate system is taken as the disturbance item of slow change, and the motor disturbance observation model is established. According to the characteristics of the observed back EMF, a phase-locked loop is designed to estimate the rotor speed and position. Through the analysis of the software simulation and physical verification results of the control model, it is proved that the observer model has high stability and adaptability for the estimation of the high and low speed operation region of the motor.
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A. Guinee, Richard. "Novel Application of Fast Simulated Annealing Method in Brushless Motor Drive (BLMD) Dynamical Parameter Identification for Electric Vehicle Propulsion." In Self-driving Vehicles and Enabling Technologies [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97370.

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Abstract:
Permanent magnet brushless motor drives (BLMD) are extensively used in electric vehicle (EV) propulsion systems because of their high power and torque to weight ratio, virtually maintenance free operation with precision control of torque, speed and position. An accurate dynamical parameter identification strategy is an essential feature in the adaptive control of such BLMD-EV systems where sensorless current feedback is employed for reliable torque control, with multi-modal penalty cost surfaces, in EV high performance tracking and target ranging. Application of the classical Powell Conjugate Direction optimization method is first discussed and its inaccuracy in dynamical parameter identification is illustrated for multimodal cost surfaces. This is used for comparison with the more accurate Fast Simulated Annealing/Diffusion (FSD) method, presented here, in terms of the returned parameter estimates. Details of the FSD development and application to the BLMD parameter estimation problem based on the minimum quantized parameter step sizes from noise considerations are provided. The accuracy of global parameter convergence estimates returned, cost function evaluation and the algorithm run time are presented. Validation of the FSD identification strategy is provided by excellent correlation of BLMD model simulation trace coherence with experimental test data at the optimal estimates and from cost surface simulation.
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Conference papers on the topic "Sensorless speed control and adaptive observation"

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Arora, Rahul, Sanjeev Singh, and Ujjwal Kalla. "Hardware Implementation of Adaptive Digital Filter based Speed and Position Sensorless Control of PMBLDC Motor." In 2025 IEEE Industry Applications Society Annual Meeting (IAS). IEEE, 2025. https://doi.org/10.1109/ias62731.2025.11061640.

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Tepe, İzviye Fatımanur, Şevki Demirbaş, and Erdal Irmak. "Design and speed sensorless adaptive maximum power point tracking control of wind turbine in stand-alone DC nanogrid." In 2025 IEEE 19th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG). IEEE, 2025. https://doi.org/10.1109/cpe-powereng63314.2025.11027289.

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Kouchih, D., M. Tadjine, and Mohamed Seghir Boucherit. "Adaptive observation of stator flux and resistance for speed sensorless DTC controlled IM drives." In 14th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA2013). IEEE, 2013. http://dx.doi.org/10.1109/sta.2013.6783187.

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Mustafa, Raihana, Zulkifilie Ibrahim, and Jurifa Mat Lazi. "Sensorless adaptive speed control for PMSM drives." In 2010 4th International Power Engineering and Optimization Conference (PEOCO). IEEE, 2010. http://dx.doi.org/10.1109/peoco.2010.5559258.

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Lee, Hou-Tsan, Li-Chen Fu, and Feng-Li Lian. "Sensorless Adaptive Backstepping Speed Control of Induction Motor." In Proceedings of the 45th IEEE Conference on Decision and Control. IEEE, 2006. http://dx.doi.org/10.1109/cdc.2006.377160.

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van Meijl, W., G. Muisers, A. Borisavljevic, M. Brands, and E. Lomonova. "Sensorless observation of a very-high-speed permanent magnet synchronous machine." In 2013 IEEE International Symposium on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics (SLED/PRECEDE). IEEE, 2013. http://dx.doi.org/10.1109/sled-precede.2013.6684502.

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Medagam, Peda V., Tansel Yucelen, and Farzad Pourboghrat. "Adaptive SDRE based nonlinear sensorless speed control for PMSM drives." In 2009 American Control Conference. IEEE, 2009. http://dx.doi.org/10.1109/acc.2009.5160104.

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Montanari, M., A. Tilli, and S. Peresada. "Sensorless control of induction motor with adaptive speed-flux observer." In 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601). IEEE, 2004. http://dx.doi.org/10.1109/cdc.2004.1428630.

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Medagam, Peda V., Tansel Yucelen, and Farzad Pourboghrat. "Adaptive SDRE-Based Nonlinear Sensorless Speed Control for PMSM Drives." In 2007 39th North American Power Symposium. IEEE, 2007. http://dx.doi.org/10.1109/naps.2007.4402359.

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You, Jie, Wencen Wu, and Yebin Wang. "An Adaptive Luenberger Observer for Speed-Sensorless Estimation of Induction Machines." In 2018 Annual American Control Conference (ACC). IEEE, 2018. http://dx.doi.org/10.23919/acc.2018.8431006.

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