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To improve the adaptability of sensorless control in the full-speed range of a dual three-phase permanent magnet synchronous motor (DTP-PMSM), an improved sensorless control strategy based on a variable-gain super twisting algorithm sliding mode observer (VGSTA-SMO) along with harmonic component compensation has been introduced in this paper. First, the super twisting algorithm sliding mode observer (STA-SMO) is introduced to reduce the inherent chattering phenomenon of traditional SMOs. Then, the variable gain of this STA-SMO is designed to improve the observation adaptability at different rotor speeds. Meanwhile, considering that the harmonic components, especially at low rotor speeds, in the stator current can affect the observation accuracy of this VGSTA-SMO, a least mean squares adaptive notch filter (LMS-ANF) is employed to implement online harmonic compensation. Finally, comparative experiments with different methods in the full-speed range are conducted and compared to verify the effectiveness of the proposed novel sensorless control strategy whose observation deviation is about 2% even when the rotor speed is as low as 100 rpm. [ABSTRACT FROM AUTHOR]

Due to the complexity of determining the initial rotor flux and detecting errors, conventional rotor flux observation methods are easily affected by direct current (DC) components and harmonics. To address this issue, this paper proposes an in-phase filter (IPF)-based rotor flux observation strategy for sensorless control of permanent magnet synchronous machines (PMSMs). The core components of the IPF consist of a double second-order generalized integrator (DSOGI) and a phase angle compensation transfer function (PACTF). The DSOGI provides a accurate electrical angular frequency, while the PACTF implements a phase correction to the v q ′ signals. By employing IPF structure, accurate observations for rotor flux, electronic speed, and rotor position are achieved, which can be effectively used in the sensorless control of PMSMs, eliminating the need for magnitude and phase compensations. Finally, the proposed observation strategy is applied to an experimental bench of a PMSM, and its effectiveness is illustrated by experimental results. From experimental results, it can be concluded that the IPF is significantly better than the LPF, and 5% more accurate than the observer based on cascade second-order generalized integral(CSOGI) overall. • The rotor position of PMSMs is estimated via rotor flux observation. • An in-phase filter is developed for rotor flux observation in sensorless control of PMSMs. • The in-phase filter is implemented on a PMSM bench. [ABSTRACT FROM AUTHOR]

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This paper proposes a modification to existing saliency-based, sensorless control strategy for interior permanent magnet synchronous motors. The proposed approach leverages a two-interval, six-segment high-frequency voltage signal injection technique. It aims to improve rotor position and speed estimation accuracy when utilizing a single current sensor positioned in the inverter's DC-bus circuit. The key innovation lies in modifying both the high-frequency signal injection and demodulation processes to address challenges in accurate phase current reconstruction and rotor position estimation, at low and zero speeds. A significant modification to the traditional high-frequency voltage signal injection method is introduced, which involves splitting the signal injection and the field-oriented control algorithm into two distinct sampling and switching periods. This approach ensures that no portion of the injected voltage space vector falls into the immeasurable region of space vector modulation, which could otherwise compromise current measurements. The dual-period structure, termed the two-interval six-segment high-frequency injection, allows for more precise current measurement during the signal injection period while maintaining optimal motor control during the field-oriented control period. Furthermore, this paper explores a different demodulation technique that improves the estimation of rotor position and speed. By employing a synchronous filter in combination with a phase-locked loop, the proposed method enhances the robustness of the system against noise and inaccuracies typically encountered in phase current reconstruction. The effectiveness of the proposed modifications is demonstrated through comprehensive simulation results. These results confirm that the enhanced method offers more reliable rotor position and speed estimates compared to the existing sensorless technique, making it particularly suitable for applications requiring high precision in motor control. [ABSTRACT FROM AUTHOR]

An online correction method for phase current sampling gain errors utilizing the phase current zero-crossing principle is proposed in this paper to solve the problems of torque/speed pulsation and inaccurate position estimation in permanent magnet synchronous motor (PMSM) drives. First, a mathematical model considering three-phase current sampling errors was built and a variable-gain sliding mode observer (SMO) was designed. Second, the impacts of current gain errors on electromagnetic torque and position estimation were analyzed. When any one of the three-phase currents crosses zero, the amplitudes of the other two-phase currents are the same but the signs are opposite. Based on this principle, the current gain ratios of these two-phase currents can be calculated. Finally, comparing three sets of current gain ratios, the faulty phase can be determined, and online correction of the current gain error is executed. Experimental results show that the proposed method can determine faults regardless of whether there is a large or small gain error. In addition, the proposed method can balance the three-phase currents, improve the accuracy of position estimation, reduce torque pulsation, and enhance the speed control performance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xi'an Jiaotong University is the property of Editorial Office of Journal of Xi'an Jiaotong University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Saw rotational speed critically influences cutting force and surface quality yet is often destabilized by variable cutting resistance. The sensorless detection method for calculating rotational speed based on current ripple can prevent the contact of wood chips and dust with Hall sensors. This paper introduces a speed control system for brushed DC motors that capitalizes on the linear relationship between current ripple frequency and rotational speed. The system achieves speed regulation through indirect speed measurement and PID control. It utilizes an H-bridge circuit controlled by the EG2014S driver chip to regulate the motor direction and braking. Current ripple detection is accomplished through a 0.02 Ω sampling resistor and AMC1200SDUBR signal amplifier, followed by a wavelet transform and Savitzky–Golay filtering for refined signal extraction. Experimental results indicate that the system maintains stable speeds across the 2000–6000 RPM range, with a maximum error of 2.32% at 6000 RPM. The improved ripple detection algorithm effectively preserves critical signals while reducing noise. This enables the motor to quickly regain speed when resistance is encountered, ensuring a smooth cutting surface. Compared to traditional Hall sensor systems, this sensorless design enhances adaptability in agricultural applications. [ABSTRACT FROM AUTHOR]

To improve the speed buffering and position tracking accuracy of medium–high-speed permanent magnet synchronous motor (PMSM), a sensorless control method based on an improved sliding mode observer is proposed. By the mathematical model of the built-in PMSM, an improved adaptive super-twisting sliding mode observer is constructed. Based on the LSTA-SMO with a linear term of observation error, a sliding mode coefficient can be adjusted in real time according to the change in rotational speed. In view of the high harmonic content of the output back electromotive force, the adaptive adjustment strategy for the back electromotive force is adopted. In addition, in order to improve the estimation accuracy and resistance ability of the observer, the rotor position error was taken as the disturbance term, and the third-order extended state observer (ESO) was constructed to estimate the rotational speed and rotor position through the motor mechanical motion equation. The proposed method is validated in Matlab and compared with the conventional linear super twisted observer. The simulation results show that the proposed method enables the observer to operate stably in a wide velocity domain and reduces the velocity estimation error to 6.7 rpm and the position estimation accuracy error to 0.0005 rad at high speeds, which improves the anti-interference capability. [ABSTRACT FROM AUTHOR]

The main goals of this research are to develop a method for obtaining the rotor position and speed in a doubly fed induction generator (DFIG) without using sensors in a variable-speed wind turbine installation. The considered method is based on the Model Reference Adaptive System (MRAS). According to this method, electromagnetic torque is used as an error variable for the adaptation process in order to refine the estimate. A good assessment is very important when trying to put into place any strategy that can control the behavior of a DFIG. This method of estimation functions by comparing the actual performance of the DFIG with that of a reference model and adjusting the system parameters to reduce any mismatch between the two. One notable advantage of this developed estimator is its stability across a broad range of speeds. Additionally, it is designed to exhibit resilience in the face of uncertainties in machine parameters. The proportional integral (PI) gains for the MRAS estimator are determined via pole placement. To assess and validate the entire DFIG model and the sensorless estimation method, comprehensive simulations are carried out using MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

This paper presents a simple and effective sensorless control strategy based on extended state observers (ESOs) to enhance the performance of brushless DC (BLDC) motors. First, an ESO is used to estimate the back-electromotive force (EMF) without additional filters. Second, another ESO is incorporated into the quadrature phase-locked loop (QPLL) to enable the implementation of an active harmonic compensator to reduce noise harmonics induced by the estimated back-EMF. By using the P-Q theory, the proposed compensator calculates a compensation signal to be directly injected into the QPLL based on ESO. The results analysis shows that the proposed strategy significantly reduces torque ripples and speed/position estimation errors under a wide range of speeds. [ABSTRACT FROM AUTHOR]

Surface-mounted permanent magnet synchronous motor (SPMSM) is widely used in the industrial field with excellent performance, and the rise of artificial intelligence has also promoted its development. In order to improve the estimation accuracy and response of speed and position angle in the SPMSM sensorless control system, a novel sliding mode control model reference adaptive system (NSMC-MRAS) observer based on variable step hill climbing method for online optimization is proposed. Firstly, an MRAS adaptive observer was constructed, and a conventional SMC controller is used instead of the PI regulator to improve the robustness of the SPMSM parameters. Aiming at the problem of chattering caused by the sign function sgn(s), an improved NSMC-MRAS sensorless control strategy using the continuous function sigmoid(s) is proposed, which effectively suppresses the chattering phenomenon. To address the position estimation errors caused by non ideal factors such as control delay, filtering phase shift, and parameter deviation, the artificial intelligence variable step hill climbing method is used for online optimization and adaptive compensation. The experimental results show that the proposed NSMC-MRAS sensorless control strategy based on variable step hill climbing method for online optimization can quickly and accurately estimate the speed and position angle of SPMSM, improved the control performance and intelligence level of the system. [ABSTRACT FROM AUTHOR]

This paper addresses performance degradation in nonlinear flux linkage algorithms, arising from estimation errors in rotor flux linkage due to fluctuations in current and temperature. We introduce a parameter-adaptive flux linkage model using MRAS, which dynamically adjusts the rotor flux linkage, significantly minimizing estimation errors and improving control performance. When the rotor flux linkage of the motor undergoes sudden changes, the nonlinear flux linkage model shows a speed fluctuation of 5%, whereas the parameter-adaptive flux linkage model reduces the error to 0.6%. The algorithm demonstrates strong robustness when the stator resistance undergoes a sudden change. The control effectiveness under conditions such as load start and load mutation is excellent. Simulations and experiments demonstrate that the parameter-adaptive flux linkage model improves the estimation accuracy of the rotor position when motor parameters change. [ABSTRACT FROM AUTHOR]

The high cost and complexity of using sensors for controlling processes have led to the development of observer techniques that aim to estimate system states without the need for sensors. These techniques reduce system complexity and can potentially reduce product and maintenance costs. In this paper, we present an interconnected high gain observer (IHGO) that estimates the electromagnetic torque, speed, and position of a doubly fed induction generator-based wind turbine (DFIG-WT) using only voltage, current, and wind speed measurements. The IHGO is designed to be robust to parameter uncertainties and its stability is assessed using Lyapunov theory. To guarantee finite time convergence, a Super Twisting-based High Order Sliding Mode (ST-HOSM) controller is used for direct torque control. The ST-HOSM is a simple algorithm that maintains the sliding mode characteristics, provides robustness against disturbance, and reduces the chattering phenomenon. The controller and observer are designed in the αβ frame to avoid the use of a phase-locked loop (PLL). Simulation results confirmed the effectiveness of the proposed control strategy under parameter uncertainties, power and speed variations, grid voltage dip and current sensor noise. [ABSTRACT FROM AUTHOR]

This paper proposes a sensorless control strategy for permanent magnet synchronous motors (PMSMs) based on a sliding mode observer (SMO), and high-speed PMSM sensorless velocity control is realized. To solve the serious chattering and phase lag problems of conventional SMOs, the continuous function is used as the control function, and the low-pass filter is improved into a back electromotive force (EMF) observer with an adaptive structure. In addition, the phase-locked loop is combined to perform the SMO-based sensorless control. The simulations and experiments prove the effectiveness of the proposed strategy.

Conventional direct torque control (DTC) improves the dynamic performance of the five-phase induction machine (FPIM). Nevertheless, it suffers from significant drawbacks of high stator flux and electromagnetic torque ripples. Moreover, the DTC technique relies on an open-loop estimator for accurate stator flux module and position knowledge. However, this method is subjected to substandard performance, mainly during the low-speed operation range. Therefore, a sliding mode sensorless stator flux and rotor speed DTC based on an artificial neural network (DTC-ANN) for two parallel-connected FPIMs is discussed to tackle the problems above. This approach optimizes the DTC performance by replacing the two hysteresis controllers (HC) and the look-up table. As for the poor estimation drawback, the sliding mode observer (SMO) offers a robust estimation and reconstruction of the FPIM variables and eliminates the need for additional sensors, increasing the system's reliability. The present results verify and compare the performance of the control scheme [ABSTRACT FROM AUTHOR]

A new predictive model reference adaptive system (MRAS) speed estimator was proposed to address the problem of the traditional proportional-integral (PI) adaptive rate in the induction machine ( IM) drive system used for shield tunneling without a speed sensor. The traditional PI adaptive rate in the MRAS system relies on manual experience adjustment and cannot adapt to model changes. The proposed estimator was based on the principles of finite control set model predictive control. A search-based optimization algorithm was adopted during the rotor speed calculation, which ensures minimum speed adjustment error signals in each sampling period and avoids the use of a proportional integral controller. Experimental results show that the proposed speed estimator has excellent dynamic and static performance over a wide speed range. [ABSTRACT FROM AUTHOR]

This paper proposes a sensorless control strategy for permanent magnet synchronous motors (PMSMs) based on a sliding mode observer (SMO), and high-speed PMSM sensorless velocity control is realized. To solve the serious chattering and phase lag problems of conventional SMOs, the continuous function is used as the control function, and the low-pass filter is improved into a back electromotive force (EMF) observer with an adaptive structure. In addition, the phase-locked loop is combined to perform the SMO-based sensorless control. The simulations and experiments prove the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

For the sensorless control in a low-speed range of synchronous reluctance motors (SynRMs), injecting random high-frequency (HF) square-wave-type voltages has become a widely used and technologically mature method. It can solve the noise problem of traditional injection signal methods. However, all injection signal methods will cause problems such as torque ripple, which causes speed fluctuations. This article proposes a self-regulating random model algorithm for the random injection signal method, which includes a quantity adaptive module for adding additional random processes, an evaluation module for evaluating torque deviation degree, and an updated model module that is used to receive signals from the other two modules and complete model changes and output random model elements. The main function of this algorithm is to create a model that updates to suppress the evaluation value deviation based on the evaluation situation and outputs an optimal sequence of random numbers, thereby limiting speed bias always in a small range; this can reduce unnecessary changes in the output value of the speed regulator. The feasibility and effectiveness of the proposed algorithm and control method have been demonstrated in experiments based on a 5-kW synchronous reluctance motor. [ABSTRACT FROM AUTHOR]

To address the problems of large sliding mode chatter and phase delay in the traditional first-order flux sliding mode observer, a HOT FSMO (High-Order Terminal Flux Sliding Mode Observer) based on an improved tracking differentiator is proposed in this study. A high-order sliding mode control law is designed to achieve chatter suppression of flux linkage estimation, and a new tracking differentiator with low chatter containing a terminal attractor is combined to replace the conventional low pass filter to achieve accurate tracking of the flux linkage and rotor position, as well as filtering functions. The experimental results show that the HOT FSMO based on the novel tracking differentiator can effectively reduce the sliding mode chattering and decrease the position estimation error, while speeding up the system response and improving the system dynamic performance under different speed and load conditions when compared with the traditional linear flux linkage sliding mode observer. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xi'an Jiaotong University is the property of Editorial Office of Journal of Xi'an Jiaotong University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In commercial electrical equipment, the popular sensorless drive scheme for the interior permanent magnet synchronous motor, based on the quasi-sliding mode observer (QSMO) and phase-locked loop (PLL), still faces challenges such as position errors and limited applicability across a wide speed range. To address these problems, this paper analyzes the frequency domain model of the QSMO. A QSMO-based parameter adaptation method is proposed to adjust the boundary layer and widen the speed operating range, considering the QSMO bandwidth. A QSMO-based phase lag compensation method is proposed to mitigate steady-state position errors, considering the QSMO phase lag. Then, the PLL model is analyzed to select the estimated speed difference for transient position error compensation. Specifically, a transient position error compensator based on a feedback time delay neural network (FB-TDNN) is proposed. Based on the back propagation learning algorithm, the specific structure and optimal parameters of the FB-TDNN are determined during the offline training process. The proposed parameter adaptation method and two position error compensation methods were validated through simulations in simulated wide-speed operation scenarios, including sudden speed changes. Overall, the proposed scheme fully mitigates steady-state position errors, substantially mitigates transient position errors, and exhibits good stability across a wide speed range. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, the use of the interior permanent magnet synchronous machine (IPMSM) in various applications has grown significantly due to numerous benefits. Sensors are used to achieve high efficiency and good dynamic response in IPMSM drives but due to their high cost and reduced overall size of the system, sensorless control techniques are preferred. Non-sinusoidal distribution of rotor flux and slot harmonics are present in the considered IPMSM. In this article, these problems are considered control system disturbances. With the above-mentioned problems, the classical observer structure based on (d-q) fails to estimate at low-speed ranges. This article proposes an observer structure based on a rotor flux vector in (α-β) stationary reference frame, which works using the adaptive control law to estimate speed and position, and a non-adaptive EEMF-based observer to estimate speed and position. Moreover, a comparative analysis between both observer structures at different speed ranges is also considered in this article. The effectiveness of the observer structure is validated by simulation tests and experimental tests using the sensorless control system with a field-oriented control scheme for a 3.5 kW IPMSM drive system. [ABSTRACT FROM AUTHOR]

To improve the accuracy of the sensorless control system for permanent magnet synchronous motors, this paper proposes the based on fractional order integral sliding mode theory in the model reference adaptive system observer. The purpose of this approach is to enhance the robustness of the system. Furthermore, this paper introduces the second-order sliding mode reaching law to suppress chattering phenomena and improve the control accuracy of the observer. Simulation results show that this strategy achieves excellent dynamic and static performance. [ABSTRACT FROM AUTHOR]

In the sensorless control of a sliding mode observer (SMO)‐based permanent magnet synchronous motor (PMSM), a large gain is required to ensure the stability of the sliding motion. Nonetheless, this can lead to the unexpected chattering and degrade the precision of position estimation. To overcome this trouble, we have proposed a fixed‐time nonsingular terminal SMO (NTSMO). The convergence time is independent of the initial value. Firstly, a fixed‐time nonsingular terminal sliding mode surface is designed so that the current observation error fixed‐time converges to zero, and the singularity issue can be averted. Secondly, via the phase‐locked loop tactic, the rotor position and speed are calculated from the measured back electromotive force. Thirdly, a Lyapunov function‐based proof is utilized to assure the stability of the observer. Finally, the validity of this method is confirmed by simulation tests and experiment results. [ABSTRACT FROM AUTHOR]

In this study, a sliding mode observer (SMO) based on high-frequency (HF) voltage signal injection and a phase-locked loop (PLL) is proposed for estimating the extended electromotive force (EEMF), rotor position, and rotor velocity of an interior permanent magnet synchronous machine (IPMSM). This approach addresses real-time estimation challenges associated with standard SMO and PLL at very low speeds and standstill. A reliable and accurate sensorless speed control system for IPMSM is then developed and implemented in real time using the proposed SMO and PLL, covering a wide range of speeds, including low-speed and standstill conditions. The SMO effectively estimates the EEMF, while the PLL extracts the rotor velocity and position based on these estimates. Compared to conventional SMO and PLL methods, real-time results from an 8-pole, 0.4 kW IPMSM demonstrate the superior efficiency of the proposed system.

When the permanent magnet synchronous motor operates at zero speed and low speed, the rotor posi- tion information can be accurately estimated by the pulse high-frequency injection method. The pulse high frequency injection method can not realize the rotor polarity judgment, while the traditional polarity judgment method has prob- lems such as long response time, complex sampling and implementation process, and even polarity misjudgment. In this study, a method of judging the rotor polarity based on positive and negative voltage pulse injection is proposed. This method injects positive and negative voltage pulses into the motor, and judges the rotor polarity according to the response current peak value of the corresponding pulse. The pulse high frequency injection method combines the rotor position estimation with the polarity judgment result to obtain the accurate initial position of the rotor. This study veri- fies the effectiveness of the algorithm through Simulink simulation. The simulation results show that the proposed rotor polarity determination method can simplify the sampling method and algorithm complexity, reduce the response time for determining rotor polarity, and enable the pulse high frequency injection method to accurately and quickly esti- mate the initial position of the rotor. [ABSTRACT FROM AUTHOR]

In permanent magnet synchronous motor (PMSM) sensorless drive systems, the motor inductance is a crucial parameter for rotor position estimation. Variations in the motor current induce changes in the inductance, leading to core magnetic saturation and degradation in the accuracy of rotor position estimation. In systems with constant load torque, the saturated inductance remains constant. This inductance error causes a consistent error in rotor position estimation and some performance degradation, but it does not result in speed estimation errors. However, in systems with periodic load torque, the error in the saturated inductance varies, consequently causing fluctuations in both the estimated position and speed errors. Periodic speed errors complicate speed control and degrade the torque compensation performance. In this paper, we propose a wavelet denoising-group method of data handling (GMDH) based method for accurate inductance estimation in PMSM sensorless control systems with periodic load torque compensation. We present a method to analyze and filter the collected three-phase current signals of the PMSM using wavelet transformation and utilize the filtered results as inputs to GMDH for training. Additionally, a method for magnetic saturation compensation using the inductance parameter estimator is proposed to minimize periodic speed fluctuations and improve control accuracy. To replicate the load conditions and parameter variations equivalent to the actual system, experiments were conducted to measure the speed ripples, inductance variations, and torque component of the current. Finally, software simulation was performed to confirm the inductance estimation results and verify the proposed method by simulating load conditions equivalent to the experimental results. [ABSTRACT FROM AUTHOR]

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Extended back electromotive force (EEMF)-based position sensorless field-oriented control (FOC) is widely utilized for ultra-high-speed surface-mounted permanent magnet synchronous motors (UHS-SPMSMs) driven fuel cell air compressors in medium-high speed applications. Unfortunately, the estimated position is imprecise due to too small EEMF under low speed operation. Hence, current-to-frequency (I-f) control is more suitable for startup. Conventional I-f methods rarely achieve the tradeoff between startup acceleration and load capacity, and the transition to sensorless FOC is mostly realized in the constant-speed stage, which is unacceptable for UHS-SPMSM considering the critical requirement of startup time. In this article, a new closed-loop I-f control approach is proposed to achieve fast and efficient startup. The frequency of reference current vector is corrected automatically based on the active power and the real-time motor torque, which contributes to damping effect for startup reliability. Moreover, an amplitude compensator of reference current vector is designed based on the reactive power, ensuring the maximum torque per ampere operation and higher efficiency. Furthermore, the speed PI controller is enhanced by variable bandwidth design for smoother sensorless transition. These theoretical advantages are validated through experiments with a 550 V, 35 kW UHS-SPMSM. The experimental results demonstrated the enhanced startup performance compared with conventional I-f control. [ABSTRACT FROM AUTHOR]