Compensation Method Research Articles

Low‐frequency oscillation damping strategy for power system based on virtual dual‐input power system stabilizer

AbstractTo keep pace with the construction of the new‐type power system, virtual synchronous generator control, as a classical method of virtual inertia control, has been widely adopted due to its electromechanical characteristics similar to synchronous generator. However, the introduction of rotor motion equations leads to low‐frequency oscillation issues in virtual synchronous generator units similar to synchronous machines. To address this challenge, this paper constructs the Phillips‐Heffron model of the virtual synchronous generator grid‐connected system and analyses the mechanism of low‐frequency oscillation in virtual synchronous generator through the damping torque method. Subsequently, a virtual dual‐input power system stabilizer is proposed by drawing inspiration from the design principles of the traditional dual‐input power system stabilizer to suppress low‐frequency oscillations in the power system. The structure of the virtual dual‐input power system stabilizer is provided, and the phase compensation method is used to optimize the parameters of the virtual dual‐input power system stabilizer. Finally, the effectiveness of the proposed virtual dual‐input power system stabilizer is verified by simulation comparison.

Variable universe fuzzy inference decided neural network feed-forward compensation for pid control of motor position

To improve the compensation accuracy of neural network decided by traditional fuzzy inference engine (FIE), a variable universe fuzzy inference (VUFI) decided neural network feed-forward compensation method for PID control of motor position is proposed. The method contains four control blocks: fuzzy inference (FI) block, variable universe (VU) block, neural network (NN) control block, and basic control block. The FI block adaptively decides the feed-forward control quantity of NN based on the error and the error change rate of control system to keep the dynamic performance of NN at the beginning of the control or the transient jump signal. The VU block constructs the contraction expansion (CE) factors from the absolute change quantity of NN weights and adjusts the universes of membership functions based on the learning situation of NN in real time so that high-precision inference can be achieved. The NN control block consists of a neural network identifier (NNI) and a neural network controller (NNC) that has the same structure with the NNI, and the NNI dynamically transfers network parameters to the NNC and outputs feed-forward compensation control quantity after learning the dynamic inverse model of DC servo motor online. The basic control block adopts a PID controller, which provides the learning samples for NN online. Experimental results proved that the proposed method can improve the inference accuracy of FIE without sacrificing steady-state accuracy, significantly reduce overshoot, and have better stability and dynamic performance.

Infinite-time optimal feedback control of a 3-phase asynchronous motor exploiting a nonlinear finite element model

This paper presents modelling of a squirrel-cage induction motor and an optimal control method based on suboptimal control for nonlinear systems to minimise consumed energy and power losses in an induction motor drive. A coupled motor model with optimal control as a closed-loop integrated system is proposed. For modelling of the squirrel-cage asynchronous machine, a field-circuit-mechanical finite-element (FE) model is employed, in which mechanical motion is realised by a moving-mesh method and fixed mesh approach. For the control problem purpose, a surrogate induction motor model, described in a stationary rotor reference d–q frame, is applied. The optimal control is realised by a nonlinear feedback compensator method based on the state-dependent Riccati equation (SDRE) with an infinite time horizon with the surrogate model state-dependent parametrisation (SDP). To perform the control strategy, a SDRE technique with Moore–Penrose pseudoinverse is adopted. To improve the accuracy of the optimisation procedure, a finite element model was used to calculate the motor performance.

Single-pixel imaging of a moving target using only Hadamard patterns for simultaneous localization and reconstruction

Relative motion degrades the image quality of single-pixel imaging (SPI) while imaging the moving targets. Motion compensation strategies are effective in improving the imaging quality. However, the existing methods often require the use of additional patterns for target localization, which increases the sampling time. What we believe is a novel motion compensation method for SPI with Hadamard geometric moments is proposed based on the sparsity of geometric moment patterns in the Hadamard domain. Parts of Hadamard patterns are used for localization and reconstruction, simultaneously, thus target localization does not require additional patterns. In addition, our method effectively improves the localization accuracy in large-scale scenes due to the absence of binarization error while enhancing the quality of the reconstructed images. Many simulations and experiments are performed to verify the accuracy and effectiveness of the proposed method and the results show that the proposed SPI system improves the imaging quality (with lower MSE and higher PSNR) while imaging moving targets in 512 × 512-sized scenes.

Analytical solution to the problem of polarization drift compensation in an all-fiber QKD system

A method for simultaneous compensation of polarization drift in a fiber-optic quantum channel, and a fully fiber-optic receiver has been successfully developed, implemented, and tested using a commercial QKD system. The method is based on the exact analytical solution we derived, which gives the necessary corrective transformation for polarization. Noise and imperfections in any realistic system require iterative application of the computed corrections. In our case, polarization drift compensation was completed on average in 2-3 iterations. This is an improvement by a factor of 10-100 compared to the common methods based on hill-climbing algorithms.

Distance deviation sensitivity on null test of convex hyperboloid mirrors with large relative aperture

In the shape measurement of convex hyperboloid mirrors with large relative apertures, alignment deviations can significantly affect the accuracy of null test results owing to their sensitivity, resulting in inaccurate results. This paper introduces autocollimation and compensation methods. Subsequently, a shape detection experiment of a large relative aperture convex hyperboloid mirror with a diameter of 15 mm was conducted using the aforementioned methods. Further, a detailed simulation analysis was performed to address the inconsistencies between the two test results. The results suggested that the Hindle sphere method was highly sensitive to distance deviation. Furthermore, the distances in the optical path exerted a complementary effect, which easily obscured the true surface shape of the measured part. The computer-generated hologram (CGH) method could accurately determine the true surface shape deviation based on the alignment judgment provided by the aligned CGH part. These studies provide scientific guidance for more accurately obtaining the true surface shape error of the hyperboloid mirror under test, and have significant engineering application value.

Ultrasound-assisted aberration correction of transcranial photoacoustic imaging based on angular spectrum theory

To correct the refraction aberration induced by the skull in photoacoustic imaging, a method for phase distortion compensation is proposed based on the angular spectrum theory with the aid of ultrasonic signals. This method first updates the speed of sound distribution by iteratively performing aberration correction in the ultrasonic reconstruction. Then the speed of sound distribution obtained with ultrasound-assisted serves as prior knowledge to address phase distortion compensation by adjusting the phase shift factor of the wavefront in different media. Finally, the aberration-corrected ultrasonic-photoacoustic dual-modality image can be obtained. Numerical simulations and phantom experiments confirm the effectiveness of this method. Specifically, in simulations, the position error of the proposed method is reduced from −13.61% to 1.27% in depth compared to the method based on the reconstruction with constant speed. Moreover, a real ex-vivo rabbit skull experiment illustrates the potential biological application of the proposed method in transcranial photoacoustic imaging.

An estimated value compensation method for state of charge estimation of lithium battery based on open circuit voltage change rate

An estimated value compensation method for state of charge estimation of lithium battery based on open circuit voltage change rate

Optical performance maintenance of solar dish collector system under service loads based on tracking compensation and receiver translational compensation methods

Optical performance maintenance of solar dish collector system under service loads based on tracking compensation and receiver translational compensation methods

Interval type-II fuzzy logic control of neutral DC compensation method to moderate DC bias in power transformer

Interval type-II fuzzy logic control of neutral DC compensation method to moderate DC bias in power transformer

A fast inverse synthetic aperture radar translational motion compensation method for low SNR scenes

Abstract Accurate translational motion compensation is crucial for inverse synthetic aperture radar (ISAR) imaging. At low signal-to-noise ratio (SNR), the performance of nonparametric methods is declining because the correlation of adjacent range profiles is severely destroyed by the noise. Fortunately, parametric methods can still work well at low SNR. However, existing parametric methods are time-consuming, which decreases ISAR imaging efficiency significantly. So, a fast parametric translational motion compensation method is studied for low SNR scenes in the paper, which is based on modified Adam (Madam) algorithm. By changing the updating strategy for weights and learning rate in Adam, Madam algorithm can significantly accelerate the convergence when estimating the motion parameters. To further improve the efficiency, a new objective function by combining image contrast and image entropy is proposed. When applied into measured Yak-42 data at low SNR, the proposed method can image about 10 times faster than particle swarm optimization (PSO) method and 2 times faster than Adam method. Therefore, the proposed method is an efficient translational motion compensation method for low SNR ISAR imaging.

A systematic review of incentive schemes and their implications for truck driver safety performance

Introduction: This systematic review investigates the effects of monetary and non-monetary incentive schemes on the safety performance of truck drivers, a critical concern within the road freight industry. Method: The review analyzes 18 studies and dissects the impact of compensation levels, compensation methods, and non-monetary benefits on drivers’ safety behaviors. Results: The findings show that, in general, higher levels of compensation, both through selection and incentive effects, enhance safety performance by attracting more skilled drivers and incentivizing adherence to safety protocols. However, the structure of these compensations, particularly piece-rate wages, and payment for non-driving hours, reveals a double-edged sword; while incentivizing productivity, they inadvertently promote unsafe driving behaviors such as excessive speeding and insufficient rest due to economic pressures. Conversely, non-monetary incentives, though under-researched, show potential for improving safety outcomes by enhancing job satisfaction and work environment quality. Practical applications: This review highlights the need for future research on safety incentives to evaluate the full extent of the intersection between incentives, safety culture, and working conditions. It advocates for holistic compensation strategies that foster a safety culture in the trucking industry, marking a new direction for improving driver behavior.

A pressure compensation method and its application in cavitation suppression of swash plate axial piston pump

A pressure compensation method and its application in cavitation suppression of swash plate axial piston pump

Advanced sensorless control of a 12S/19P YASA-AFFSSPM motor using extended state observer and adaptive sliding mode control

This paper focuses on enhancing the sensorless control performance of a 12slots/19 poles yokeless and segmented armature axial flux-switching sandwiched permanent-magnet motor by proposing a rotor position Extended State Observer based on a extended back-EMF model method. Additionally, an adaptive sliding mode speed loop compensation method is introduced to address the significant cogging torque of the motor. By injecting the observed cogging torque as compensation into the q-axis current harmonic, this method aims to improve the motor's vibration and disturbance rejection performance in sliding mode control while eliminating steady-state errors in rotor speed and position estimation. The effectiveness of these control algorithms is validated through simulations and experiments under various operating conditions, demonstrating their potential for improving the position signal-free tracking performance of the investigated motor. The results indicate that the proposed control strategies achieve a maximum speed estimation error of approximately 1 rpm during steady-state operation and a maximum position estimation error of about 1.5°, showcasing high accuracy and robustness against disturbances.

A hybrid active control method for a 3-DOF wave-compensated gangway

ABSTRACT Wave-compensated gangways are affected by forces from internal joint coupling and vessel motion, making the control process complex and challenging. Previously, three-degree-of-freedom gangways adopted passive compensation methods, utilizing end-effector sensor feedback for control. However, these methods are constrained by slow response times and significant lag. This study proposes an active hybrid compensation approach to enhance response speed and reduce tracking errors. The kinematics and dynamics of the gangway under vessel motion were analyzed. Subsequently, an improved velocity feedforward second-order super-twisting sliding mode control scheme was designed, complemented by fuzzy control for small torque compensation. Two experiments were conducted to evaluate and compare the performance of three control methods. Experiments demonstrated that the proposed hybrid control method exhibited superior performance in joint trajectory tracking, significantly reducing both root mean square and maximum errors, validating its effectiveness in improving tracking speed and accuracy.

Error compensation for industrial robots combining kinematics characterized by conformal geometric algebra and fused observability-index-based measurement strategy

Abstract The geometric errors of industrial robots are key factors affecting positioning accuracy. A new compensation method for industrial robots is proposed based on the kinematics characterizing with Conformal Geometric Algebra (CGA) and measurement strategy with Double Ball Bar (DBB) path point optimization. Firstly, a kinematic error model for the industrial robot is established using CGA, the starting point of the CGA model is modified to simplify the modeling process and reduce computational complexity. Secondly, fused observability index is proposed and the relationship between the number of sampling points on the DBB path and the effectiveness of error parameter is obtained. Thirdly, the adaptive golden spiral optimization algorithm for error parameter identification is proposed, achieving efficient and stable identification of error parameters. Finally, a case study is carried out on a six-degree-of-freedom industrial robot. The validity of measurement strategy and error parameter identification algorithm are confirmed by comparing the residuals and uncertainties of predicted point positions in space with different methods. The spatial compensation results show that, after compensation, the average error and root mean square error of measurement paths are reduced by 36.76% and 33.96%, respectively.

Guaranteed Disturbance Compensation and Robust Fault Detection Based on Zonotopic Evaluation

ABSTRACTIn the context of model‐based fault detection, it is crucial to achieve strong robustness against disturbance and noise. However, the existing robust fault detection methods typically address disturbance and noise in a centralized manner to enhance robustness, which may cause some conservatism since the dynamic characteristics of disturbance and noise are considerably different. In addition, most of the existing model‐based fault detection method is implemented with constant thresholds, which may further introduce conservatism. In this context, this paper proposes a guaranteed disturbance compensation and robust fault detection method based on zonotopic evaluation for the discrete‐time systems subject to unknown but bounded disturbance and noise. To this end, a disturbance compensation controller is developed based on technology to obtain guaranteed control performance. Moreover, the control performances with or without disturbance compensation are analyzed based on zonotopes. By considering the disturbance dynamic characteristics, an extended fault detection observer (EFDO) is created to pursue robustness to disturbance, noise, and sensitivity to fault simultaneously. Meanwhile, a multi‐objective EFDO is devised by exploiting the index and index as the criteria within the finite‐frequency domain. Furthermore, the zonotopic residual evaluation is further deployed to generate the residual boundary, which helps to reduce the conservatism of fault detection. The superiority of the proposed method is theoretically analyzed. Simulation results also validate the effectiveness and superiority of the proposed method in disturbance compensation fault detection.

A Meta-Analysis of Salary Benchmarking of Engineers, BIM Modelers, and BIM Managers in the Philippines

This study provides a detailed meta-analysis of salaries for engineers, BIM modelers, and BIM managers in the Philippines, emphasizing how geographical location, experience level, industry sector, qualifications, and market trends influence compensation. The analysis incorporates data from a variety of sources, including academic publications, industry reports, and government statistics, to provide a detailed understanding of salary variations within different professions. Findings show significant salary differences based on their geographical location. Professionals in Metro Manila have considerably larger wages than those in provincial re-gions. Experience level is also important when it comes to salary increas-es which can be observed when professionals advance from entry-level to senior roles. Salary levels are also influenced by the industry, with tech-nology, building, and infrastructure development sectors offering highest compensation. Additional qualifications and certificates enhance salary opportunities, reflecting the value of particular skills and expertise. The purpose of this study is to write a meta-analysis of salary benchmarks for BIM modelers, engineers, and BIM managers in the Philippines emphasiz-ing how factors such as geographical location, experience level, industry sector, qualifications, and market trends influence compensation. The analysis includes seven studies that were published between 2019 and 2024 to capture recent salary patterns in these professions. The study shows the importance of understanding these important variables in de-veloping successful compensation methods, optimizing talent acquisition, and promoting retention in the engineering and construction sectors in the Philippines. The insights provided are expected to allow stakeholders to make informed decisions to build a competitive and thriving workforce in these critical industries.

A High-Precision Temperature Compensation Method for TMR Weak Current Sensors Based on FPGA

A High-Precision Temperature Compensation Method for TMR Weak Current Sensors Based on FPGA

Precision compensation method for large-scale measurements based on full-space refractive index field reconstruction with vibratory mirror background oriented schlieren (VMBOS)

With the development of the large-scale equipment manufacturing industry, such as aircraft component assembly, wind turbine rotor blade measurement and large ship assembly the demand for optical measurement accuracy in large-dimensional spaces within industrial environments has become increasingly stringent. However, due to the presence of internal interference sources, light will no longer propagate in a straight line, thereby introducing measurement errors that cannot be ignored. To compensate for the measurement error, the refractive index field distribution within the large-dimensional measurement space must be reconstructed. Therefore, this paper proposed a vibratory mirror background oriented schlieren (VMBOS) based on vibratory scanning. This method scans the measurement space through the rotation of vibratory mirror to obtain light deflection angles at different directions. Subsequently, the refractive index field of the large-dimensional space is reconstructed by using the tomographic reconstruction algorithm. Then the optical path of the light in the optical measurement can be corrected through the Hamiltonian ray tracing algorithm, thereby achieving compensation for the measurement error. Finally, the VMBOS method has been verified through both simulation and experimental methods. The experimental results demonstrated that the method proposed in this paper can be applied to optical path correction and error compensation in large scale spaces.