Sensorless Technique Research Articles

A voltage sensorless technique for a shunt active power filter adopting band pass filter under abnormal supply conditions

Shunt active power filters (SAPFs) are effective in addressing power quality issues such as harmonics and voltage unbalance. During abnormal grid conditions, there will be a substantial variation in both the actual and reactive power of the system. Various SAPF control approaches were employed to address these issues. This paper presents an improved bandpass filter technique that serves multiple purposes: extracting the reference current harmonic for SAPF, providing reactive current for power factor correction, and functioning as a backup synchronization method in the event of a loss of bus voltage measurement. Furthermore, it should be minimally affected by the unbalance in supply voltage. The case study model and the proposed reference technique have been executed and validated using the MATLAB software environment.

Research on Fourier Coefficient-Based Energy Capture for Direct-Drive Wave Energy Generation System Based on Position Sensorless Disturbance Suppression

In order to improve the energy capture efficiency of direct-drive wave power generation (DDWEG) systems and enhance the robustness of the reference power tracking control, a Fourier coefficient-based energy capture (FCBEC) and a position sensorless disturbance suppression (PSDS) control strategy are proposed. For energy capture, FCBEC is proposed to construct the objective function by maximizing the average power over a period of time and expanding the variables in the Fourier basis when the maximum power is captured, which is used as the basis for obtaining the reference trajectory. To address the limitations of the mechanical encoder, the position sensorless technique, based on a sliding mode observer (SMO), is used in the power tracking control, and the position information is obtained through an inverse tangent function. The perturbation caused by the inverse electromotive force error in the system is theoretically analyzed. A full-order terminal sliding mode approach is employed to design a current controller that suppresses the perturbation and ensures accurate tracking of the reference current. Simulation results show that the ocean-wave energy capture strategy proposed in this paper can make the energy captured by the PTO reach the optimal value under the impedance matching condition, and that the response speed and robustness of the full-order terminal sliding mode are better than the traditional PI control.

Speed control of PM brushless DC motor using sensorless hybrid controller

In most industrial processes, rising productivity necessitates increased demand on electrical motors in order to minimize costs and improve drive system efficiency. The sensorless technique is preferred. Brushless DC (BLDC) motors compete with a wide range of different motor types in the motion control industry. The nonlinearity of BLDC motor characteristics is challenging to manage with a traditional proportional integral derivative (PID) controller. The PID controller's fuzzy logic allowed it to tune itself while operating online. Hybrid approaches outperform stand-alone algorithms because they can overcome their weaknesses without losing their advantage. The purpose of this study is to present a fuzzy PI+D controller that is simulated over a wide range of reference speeds, loads, and parameter variations. This paper presents a model of a sensorless BLDC motor with a speed controller. The responses of the rotor speed, electromagnetic torque, stator back electromotive force (EMF), and stator currents are effectively monitored. The findings from the simulation indicate that the hybrid controller presented in this study exhibits resilience to rapid load torque and parameter fluctuation. Furthermore, it demonstrates superior dynamic performance and exhibits notable enhancements in speed tracking and system stability. The performance of the system is enhanced through the utilization of the proposed hybrid intelligent controller.

Sensorless model-based displacement estimator for piezoelectric actuator through a practical three-stage mechanism

Piezoelectric elements (PEMs) are used in a variety of applications. In this paper, we developed a new simple sensorless method for a Piezoelectric Actuator (PEA), which includes piezostack elements and a three-stage amplification mechanism.This research focuses on a piezoelectric actuator that incorporates a three-stage amplification system, where the outcome of one stage serves as the input for the subsequent one. The actuator receives two types of inputs: the voltage applied to the piezoelectric elements and the mechanical load it carries. Its output is defined by the rotation angle observed at the end of the third amplification stage. To indirectly measure the actuator's displacement, a basic external circuit is utilized.The precise movement of these actuators is essential. To circumvent the high costs and limitations associated with highly accurate displacement sensors, there has been a growing interest in sensorless control methods. Certain electrical signals, when measured, can provide an estimation of displacement. However, induced voltage measurements are not effective for piezoelectric stacks. Two more promising measures are the voltage and current of the piezoelectric material.Given that the electrical charge on these actuators closely reflects their displacement with minimal hysteresis across a broad frequency spectrum, it's proposed that displacement can be effectively gauged through current measurements that assess charge.The core contribution of this paper is the introduction and validation, both theoretically and experimentally, of a hybrid algorithm that leverages these two electrical signals to enhance the accuracy of displacement estimates. This was confirmed using a laboratory setup.The primary benefit of this research is the presentation of a straightforward sensorless control algorithm, poised for further exploration within the realm of piezoelectric actuators. The simplicity of both the theoretical model and the sensorless technique facilitates their application across a diverse range of piezoelectric actuators and amplification systems, thereby streamlining the design, modeling, and control strategy development for various actuators.The innovation of this study stems from the application of an uncomplicated sensorless estimation algorithm, coupled with a system-level perspective on piezoelectric actuators. This approach utilizes a simple, adaptable model suitable for a wide array of applications and operational techniques.

Dynamic Performance Evaluation of a Brushless AC Motor Drive Using Different Sensorless Schemes

The presented study concerns with evaluating the dynamic performance of an isotropic sinusoidal brushless motor drive while utilizing different sensorless schemes. Three estimation algorithms are considered: the first depends on extracting the speed and position via comparing two values of motor's voltage in two co-ordinate systems; the second extracts the speed and position signal via comparing two different values of motor's current defined in two co-ordinates; while the third depends on estimating the motor's flux and use it to get the speed and position. The vector control is adopted to manage the drive dynamics. The detailed mathematical derivations for all system components are presented to facilitate the performance analysis. The theoretical base of each sensorless scheme is also described in detail. The target of the provided comparative analysis is to outline the weakness and strength points of each adopted sensorless schemes while estimating the speed and rotor position for a wide operating speed range. The judgment is measured in terms of the speed and rotor position estimation errors and the dynamic response as well. The performance evaluation process is carried out using MATLAB/Simulink software in which all system parts are simulated using their mathematical models. The findings from the study state that when it comes to dynamic speed behaviour, the voltage-based sensorless technique dominates, while the current-based sensorless approach gives stability in speed estimate priority. Alternatively, the third adopted sensorless scheme offers an acceptable high-speed performance and respectable performance at lower speeds. Statistically, it is found that the voltage-based estimation technique gives respectively lower speed and position estimation errors with percentages of 35% and 10% lower than their values under the current-based estimation technique, and with percentages of 35% and 30% lower than their values under the third adopted scheme.

Sensorless control of permanent magnet synchronous motor for exhaust energy recovery of internal combustion engine: a comparison between Kalman filter and MRAS observer

This paper deals with the sensorless control of a Permanent Magnet Synchronous Motor (PMSM) to be employed on a turbo-generator to recover the exhaust gas energy of an Internal Combustion Engine (ICE). The main problem with this application is the high rotational speed required by the exhaust gas turbo-generator. Indeed, this implies the difficulty of installing an encoder for speed measurement and control. For this reason, sensorless control is highly recommendable, but, on the other hand, the main sensorless techniques could fail in this peculiar situation because of the high computational effort required compared with the other sensorless applications. Moreover, a good knowledge of the model parameters is necessary. Therefore, the main goal of this paper is to compare two main sensorless techniques for rotational speed measurement, both in the deterministic framework (Model Reference Adaptive System (MRAS) observer) and stochastic framework (Extended Kalman Filter (EKF)), to verify their effectiveness, their computational load, their sensitivity against parameter variation and noisy measurements, and, finally, to present the best solution for the exhaust gas energy recovery from the internal combustion engine.

Intelligent fuzzy back-stepping observer design based induction motor robust nonlinear sensorless control

Introduction. The control algorithm of Induction Motor (IM) is massively dependent on its parameters; so, any variation in these parameters (especially in rotor resistance) gives unavoidably error propagates. To avoid this problem, researches give more than solution, they have proposed Variable Structure Control (VSC), adaptive observers such as Model Reference Adaptive System, Extended Luenberger Observer (ELO) and the Extended Kalman Filter (EKF), these solutions reduce the estimated errors in flux and speed. As novelty in this paper, the model speed observer uses the estimated currents and voltages as state variables; we develop this one by an error feedback corrector. The Indirect Rotor Field Oriented Control (IRFOC) uses the correct observed value of speed; in our research, we improve the observer’s labour by using back-stepping Sliding Mode (SM) control. Purpose. To generate the pulse-width modulation inverter pulses which reduce the error due of parameters variations in very fast way. Methods. We develop for reach this goal an exploration of two different linear observers used for a high performance VSC IM drive that is robust against speed and load torque variations. Firstly, we present a three levels inverter chosen to supply the IM; we present its modelling and method of control, ending by an experiment platform to show its output signal. A block diagram of IRFOC was presented; we analyse with mathematic equations the deferent stages of modelling, showed clearly the decoupling theory and the sensorless technique of control. The study described two kinds of observers, ELO and EKF, to estimate IM speed and torque. By the next of that, we optimize the step response using the fuzzy logic, which helps the system to generate the PI controller gains. Both of the two observers are forward by SM current controller, the convergence of SM-ELO and SM-EKF structures is guaranteed by minimizing the error between actual and observed currents to zero. Results. Several results are given to show the effectiveness of proposed schemes.

Comparative vector control study on speed of PMSM drive using sensorless and machine learning techniques: review

The main contribution of this review work is to show how various control techniques are used to manage the speed of Permanent Magnet Synchronous Motor (PMSM). The PMSM’s are mostly used in electric vehicles, electric traction and high performance industrial drive applications. In this article conventional sensorless techniques are compared with machine learning techniques such as fuzzy logic, artificial neural network and neuro-fuzzy controllers to control the speed of PMSM drive based on vector control approach. The benefits of machine learning techniques used in sensorless PMSM drive are easy to design, less execution time and fast access speed control. The various controlling techniques used in controller along with its complexity, advantages and drawbacks are discussed in this article. The above mentioned controlling techniques are implemented and simulated by using MATLAB R2019b/Simulink software based on sensorless Model Reference Adaptive System (MRAS) with the help of Field Oriented Control (FOC) strategy of PMSM drive. By comparing the all sensorless controlling techniques in simulation study, it is identified that the combination of neuro-fuzzy controller gives the best speed control performance than other controllers.

Virtual Hall sensor triggered multi-MHz endoscopic OCT imaging for stable real-time visualization.

Circumferential scanning in endoscopic imaging is crucial across various disciplines, and optical coherence tomography (OCT) is often the preferred choice due to its high-speed, high-resolution, and micron-scale imaging capabilities. Moreover, real-time and high-speed 3D endoscopy is a pivotal technology for medical screening and precise surgical guidance, among other applications. However, challenges such as image jitter and non-uniform rotational distortion (NURD) are persistent obstacles that hinder real-time visualization during high-speed OCT procedures. To address this issue, we developed an innovative, low-cost endoscope that employs a brushless DC motor for scanning, and a sensorless technique for triggering and synchronizing OCT imaging with the scanning motor. This sensorless approach uses the motor's electrical feedback (back electromotive force, BEMF) as a virtual Hall sensor to initiate OCT image acquisition and synchronize it with a Fourier Domain Mode-Locked (FDML)-based Megahertz OCT system. Notably, the implementation of BEMF-triggered OCT has led to a substantial reduction in image jitter and NURD (<4 mrad), thereby opening up a new window for real-time visualization capabilities. This approach suggests potential benefits across various applications, aiming to provide a more accurate, deployable, and cost-effective solution. Subsequent studies can explore the adaptability of this system to specific clinical scenarios and its performance under practical endoscopic conditions.

Synchronization Techniques Comparison for Sensorless Control applied to PMSG

This paper encompasses a comparative study of techniques for position and speed estimation applied to permanent magnet synchronous generators (PMSG), connected to the distribution grid by means of a back to back converter. In the context of low and medium power wind energy conversion systems, the robustness of the sensorless techniques are studied taking into account the tolerance of the PMSG parameters.

Effects of the Mutual inductances on the Switched Reluctance Machines

There are many studies which discuss the mutual inductances in the Switched Reluctance Machine – SRM. Most of these studies said that the influence of inductance is negligible. In this paper the influences of those inductances are analyzed. This work presents experimental measures and analysis of these quantities on prototypes of SRM with various settings aiming to contribute to the knowledge of the subject. The variations of the inductance profile due to the current in the active phase, the angular position of the rotor and saturation are taken into account. Surfaces are presented to summarize the behavior of the self inductance and of the mutual inductances gotten from different machines. It is presented the simulation of the SRM in generator mode taking into account the mutual inductances. The results are presented and discussed conclusively, and then some propositions are made. The results presented here reveal the relative dimension and the influence of the mutual inductances and show that they have the potential to indicate the position of the rotor of the machine, thus avoiding the use of electronic sensors allowing sensorless techniques. Furthermore, this article highlights the importance of considering the mutual inductances in the design, mathematical modeling and simulation of SRM in order to improve de machine performance.

New Autonomous Sensorless Technique for Five Phase Permanent Magnet Motor Drive System From Perspective of Flux Intensifying Effect and ADRIL Observation

New Autonomous Sensorless Technique for Five Phase Permanent Magnet Motor Drive System From Perspective of Flux Intensifying Effect and ADRIL Observation

Super-Twisting MRAS Observer-Based Non-linear Direct Flux and Torque Control for Induction Motor Drives

Abstract This research paper proposes a novel design of an efficient combined sliding mode observer (SMO) for induction motor flux and speed estimation. The suggested sensorless technique employs the sliding mode’s second-order approach using a model reference adaptive system (MRAS). The second-order super-twisting control method is free-chattering, which lowers the chattering effect while preserving the same good features as the first-order sliding mode control (SMC). In addition, the conjunction with the MRAS as a separated speed estimator can raise the accuracy and make the observer immune to speed fluctuations, particularly for low-speed applications. Furthermore, in order to achieve effective decoupled flux–torque control, the super-twisting algorithm (STA) was combined with a non-linear feedback linearisation controller for the inner control loop construction. This strategy can boost the control system’s stability and robustness against external disturbances and modelling uncertainty. The performance analysis of the suggested methods has been carried out via simulation and experimental validation utilizing MATLAB/Simulink with the dSpace 1104 real-time interface.

Review of Control Topologies for Flux Switching Motor

Flux switching Motor (FSM) was invented in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$19^{th}$ </tex-math></inline-formula> century but started gaining importance after 2000. The simple structure and moderate cost of FSM, in comparison with existing commutated Direct Current (DC) and Permanent Magnet Brushless Direct Current (PMBLDC) motors, have made it attractive for contemporary applications. Currently, FSM is employed in research applications like automobiles, domestic appliances, power generation, etc. To make FSM a viable candidate for these applications, modifications are made to the design, power converters, and control systems of FSM. This article comprehensively reviews the various control topologies adopted for FSM, which encompasses the control of torque and speed. Different control algorithms like 1) linear controllers, 2) sensorless techniques, 3) predictive controllers, and 4) optimization techniques are discussed extensively based on existing literature. Further, a case study is carried out using these control algorithms, and the simulation results are analyzed.

An IoT and Semi-Supervised Learning-Based Sensorless Technique for Panel Level Solar Photovoltaic Array Fault Diagnosis

The performance of solar photovoltaic (SPV) systems is significantly affected by faults in the SPV arrays. Changes in environmental conditions and nonlinear characteristics of solar cells make it challenging to identify faults by conventional protection schemes. Existing learning-based fault diagnosis approaches require voluminous data and sensors, making them costly and challenging to integrate with existing SPV systems. Moreover, the lack of panel-level monitoring in existing approaches renders them incapable of pinpointing the precise location of the faulty panel. To address these issues, this paper proposes a methodology for detecting faults, localizing the exact faulty panel, and accurately classifying faults in SPV arrays. The methodology involves a sensorless electronic circuit using a bipolar junction transistor and Zener diode for fault detection, an IoT-based web application for monitoring individual solar panels for fault localization, and a deep autoencoder-based semi-supervised learning module followed by a hybrid support vector machine and logistic regression for fault classification. The proposed methodology is a low-cost and less data-intensive solution that results in precise fault detection, exact faulty panel localization, and fault classification with an overall accuracy of 99.67%. The methodology is validated in a laboratory-scale real-time setup of a grid-connected SPV system under varying electrical and environmental conditions.

An Adaptive Fault Diagnosis of Electric Vehicles: An Artificial Intelligence Blended Signal Processing Methodology

This article demonstrates an innovative design of a sensorless technique to diagnose, monitor, and broadcast faults in an electric vehicle’s (EV) propulsion operating conditions. By utilizing the artificial intelligence with a signal processing mixed clustering technique, an onboard health monitoring system (HMS) has been presented. The clustering technique uses a data-mining approach to prevent future failures for predictive maintenance planning, which is novel. For example, the propulsion inverter is equipped with a diagnostic system that uses the proposed algorithm to compare the reference gate-driving signal with the actual output voltage of the voltage source inverter (VSI). This article presents different failure scenarios of the inverter and demonstrates the capability to be applied to other components, such as brakes and motors. To validate the proposed technique, the necessary algorithm calculations, simulation, and laboratory prototype results are provided. The proposed work is proven accurate with fast response in healthy and faulty conditions.

Design and Implementation of a Driving Strategy for Star-Connected Active Magnetic Bearings with Application to Sensorless Driving

For decades, sensorless position estimation methods gained lots of interest from the research community, especially in the field of electric drives and active magnetic bearings (AMBs). In particular, the direct flux control (DFC) technique promises unique advantages over other sensorless techniques, such as a higher bandwidth, but on the other hand, it requires the coils to be connected in a star topology. Until now, star-point connections are rarely found on active magnetic bearings. In consequence, there is no known publication about the application of the DFC to an AMB to this date. In order to apply the DFC to an AMB, a star-point driving approach for AMBs must be developed beforehand. A star-connected driving approach, capable of driving a four-phase AMB, is proposed and validated against traditional H-bridges in a simulation. Further, the strategy is tested in a physical application and generalised for 4∗n phases. In terms of current dynamics, the simulation results can be compared to the well-known full H-bridge driving. The experiments on the physical application show that the actual current in the coils follows a reference with satisfactory accuracy. Moreover, the inductance measurements of the coils show a strong dependency on the rotor’s position, which is crucial for sensorless operation. A star-point connection delivers a satisfying response behaviour in an AMB application, which makes sensorless techniques that require a star point, such as the DFC, applicable to active magnetic bearings.

A SDTOGI based speed control method for SPMSG in WECS

Abstract The sensorless techniques are incorporated to optimize the cost and performance of the Surface Mounted Permanent Magnet Synchronous Generator (SPMSG) in the Wind Energy Conversion System (WECS) in this manuscript. Strengthen Dual third-Order Generalized Integrator (SDTOGI) with Synchronous Reference Frame-Phase Locked Loop (SRF-PLL) is applied in SPMSG to estimate the speed &amp; position of the measured generator stator current. The proposed technique is applied in low-speed direct-driven 1.5 MW SPMSG. SDTOGI with SRF-PLL technique is compared with conventional techniques to investigate the efficacy of the proposed sensorless technique due to rapid change in the torque of the turbine. The stability of the proposed system is higher, as shown in the Nyquist plot. Further, the obtained simulation result shows that the proposed method estimates position and speed efficiently. The results are verified in the OPAL-RT 4510 real-time simulator environment to ensure the efficacy of the proposed technique.

A Novel Constant Power Factor Loop for Stable V/f Control of PMSM in Comparison against Sensorless FOC with Luenberger-Type Back-EMF Observer Verified by Experiments

This paper proposes a novel constant power factor loop in the V/f control strategy with stabilization for a permanent magnet synchronous motor (PMSM). The advantage of such an algorithm is the independence of the machine parameters, which vary under different operational conditions, e.g., with temperature, magnetic core saturation, and skin-effect. Furthermore, it is a low-cost and simple-to-implement sensorless solution. The proposed strategy is compared against traditional sensorless FOC with a Luenberger-type back-electromotive force (EMF) observer, which can be designed based on the machine model. The output of this kind of observer is typically an error signal, which can be specified for position deviation, requiring phase-locked loop (PLL) algorithm implementation. Employing PLL, a rotor speed and position can be estimated from such an error. Therefore, it is a complex sensorless technique with high-performance microcontroller unit (MCU) requirements. Both strategies are deeply analyzed, mathematically described, and compared within the paper. At the end of the paper, these sensorless strategies are supported by experimental verification with a traction PMSM designed for golf cart applications, and the pros and cons of both techniques are discussed.

Grid-Voltage Sensorless Model-Free Predictive Current Control for PWM Rectifiers With Measurement Noise Suppression

This article investigates the performance of model-free predictive current control (MFPCC) with different sampling frequencies and measurement-noise conditions. It shows that the performance of MFPCC can be degraded seriously even if the stagnant current variation update is removed because the current variations for the MFPCC design are highly sensitive to measurement noise, especially at high sampling frequency. In order both to overcome this problem and to remove the stagnant current variation update, we propose an enhanced MFPCC for pulsewidth modulation rectifiers. In the proposed method, the stagnant current variation update is removed by updating the intermediate terms to reconstruct all current variations, while noise involved in the current variations is suppressed with the aid of an second-order generalized integrator filter. As a result, high control performance is achieved with the proposed method even if a very high sampling frequency is used, in contrast to previous MFPCC methods. In addition, a new grid-voltage sensorless technique was also developed for the proposed MFPCC. Simulation and experiment results under both normal and distorted grid conditions are provided to verify the effectiveness and robustness of the proposed method.