Search Results (56)

This study presents a novel cooperative control strategy designed to mitigate torque ripple and enhance the disturbance rejection capability of switched reluctance motors (SRMs). The proposed approach integrates model predictive control (MPC) with direct instantaneous torque control (DITC), leveraging the torque sharing function (TSF) to generate phase-specific reference torque profiles. MPC employs rolling optimization to compute the optimal duty cycle in real time, achieving low torque ripple and consistent switching frequency during steady-state operation. To overcome the inherent delay in MPC’s dynamic response, DITC is incorporated as a fast-acting compensation loop that activates immediately upon detecting abrupt variations in speed or load, thereby delivering rapid torque adjustment and reinforcing system resilience. For validation, an 8/6-pole SRM control model was developed using Ansys/Maxwell and MATLAB/Simulink, and subjected to multi-scenario simulations. The results reveal that, compared to conventional MPC, the proposed method reduces steady-state torque ripple by 19.4% and shortens dynamic recovery time by 40%, demonstrating superior torque smoothness and improved robustness against external disturbances. Full article

Permanent magnet synchronous machines (PMSMs) are widely used in high-performance drive systems. However, parasitic torque ripple remains a critical limitation, causing acoustic noise, mechanical vibration, and speed fluctuations. This study presents a compact, model-based torque control strategy for surface-mounted PMSMs (SPMSMs) that suppresses torque ripple by generating a structured current reference. Grounded in the magnetic co-energy principle, the proposed method utilizes a deterministic analytical model to compensate for cogging torque and inductance harmonics, avoiding computationally intensive iterative estimators. A primary contribution involves adapting the harmonic injection profile to varying loads and magnetic saturation levels. Comprehensive finite element analysis (FEA) co-simulations demonstrate that the proposed method reduces torque ripple by approximately 87.5% and speed ripple by over 90% at 1500 RPM compared to conventional maximum torque per ampere (MTPA) strategies. Furthermore, extended dynamic analysis confirms superior robustness during start-up, transients, and low-speed operation (100 RPM), maintaining high control authority even under deep magnetic saturation (2.0 p.u.). Performance evaluations verify that this significant enhancement in torque quality is achieved with a negligible increase in total power losses (~2.1%), presenting a computationally feasible solution for industrial embedded platforms. Full article

Conventional pneumatic precision planters still face challenges in combining high-speed operation with accurate seed placement and embryo protection under zero-velocity seeding conditions. This study presents a dual-motor rotating–throwing seed-metering device that simultaneously overcomes these challenges. Instead of relying on conventional imprecise airflow to generate initial velocity, seeds are accelerated and released by a motor-driven spoon with precisely defined kinematic profiles. By accurately controlling seed-throwing velocity and angle, the system compensates for the forward motion of the machine to achieve zero-velocity seeding and accurate landing point control across the full speed range. The elimination of seed tubes prevents frictional embryo damage, particularly benefiting fragile seeds such as cotton or peanuts. High-speed imaging (1000 fps) verified uniform initial seed ejection conditions, stable trajectories, and landing position errors below 1.5 cm at 7–13 km/h. The proposed electromechanical approach provides accurate metering, zero-velocity seeding, and seed protection under high-speed conditions, overcoming the inherent limitations of airflow-dependent systems and offering a robust alternative for precision agriculture. Compared with conventional pneumatic meters, the proposed system reduced seed landing variation by over 50%, demonstrating superior robustness under 7–13 km/h operation. Full article

To investigate the hot deformation characteristics of the Al–10Mg–3Zn alloy, a series of hot compression tests was carried out using a Gleeble-3500 simulator. The experimental matrix covered temperatures of 300–450 °C and strain rates from 0.001 to 10 s⁻¹. The true stress–strain curves were obtained and the hot processing map of the alloy was constructed based on the Dynamic Material Model principle. The multi-objective optimization of the extrusion process parameters was performed using the response surface method. The results showed that the flow stress of Al–10Mg–3Zn alloy increased with the increase in the strain rate and decreased with the increase in the deformation temperature, indicating that the alloy had a positive strain rate sensitivity. A strain-compensated Arrhenius constitutive model and a hot processing map of Al–10Mg–3Zn alloy were established based on the temperature-corrected data; here, the optimal temperature range and strain rate range for hot processing were specified. The optimal extrusion process parameters, determined by the response surface method, were as follows: billet temperature of 400 °C, extrusion speed of 0.20 mm/s, and ingot length of 350 mm. With this parameter combination, the simulation predicted an extrusion load of 73.29 MN, a velocity deviation of 24.96%, and a cross-sectional temperature difference of 9.48 °C for the profile. The predicted values from the response surface method were highly consistent with those from the finite element simulation. The optimized process parameters significantly reduced the extrusion load of the profile. Full article

Stepped-carrier orthogonal frequency division multiplexing (SC-OFDM) radar is an emerging low-cost alternative to standard OFDM radar for automotive applications due to providing high-range resolution at a low sampling rate. However, it is limited by inter-carrier interference (ICI) and velocity ambiguity in high-speed target detection. To address these issues, this paper proposes a two-step method for SC-OFDM radar. The method first applies multi-hypothesis Doppler compensation and leverages peak sidelobe ratio (PSLR) in the range profile as a distinguishing feature to estimate the target’s unambiguous velocity. Then, target signals are reconstructed into components free from ICI. Simulation results confirm the effectiveness of the proposed method. Compared to existing methods, this approach eliminates ICI without repeating OFDM symbols, thereby preserving communication data rate and enhancing suitability for integrated sensing and communication (ISAC) applications. Full article

Pre-defined motion command profiles enable precise positioning and dynamic control in mechanical and mechatronic systems, maximizing efficiency and reliability. Real-world applications introduce dynamic factors like mechanical compliance, friction, and external disturbances that significantly impact system performance. Understanding these influences improves motion control strategy accuracy, robustness, and system stability. This study emphasizes the role of systematic and stochastic disturbances in improving motion control and accuracy. It introduces a structured method for evaluating system behavior under realistic operational conditions using advanced vibration analysis and spatio-temporal similarity measures. Using vibration indicators like amplitude, frequency content, phase relationships, crest factor, and acceleration root mean square (RMS) values, a comprehensive framework is created to quantify motion profile deviations. These indicators identify resonant frequencies, transient disturbances, and system inconsistencies, improving compensation strategies and predictive maintenance. A key contribution of this research is the comparison of quantification methods for motion precision and robustness integrating vibration diagnostics and advanced motion similarity analysis to improve motion control and assessment. Multi-faceted motion deviation characterization is achieved by combining displacement, velocity, and acceleration measurements with statistical and mathematical analysis. To assess motion consistency, spatio-temporal similarity measures like Dynamic Time Warping (DTW), Hausdorff distance, and discrete Fréchet distance capture spatial alignment and temporal progression. These measures allow a more nuanced evaluation of motion quality than traditional error metrics, especially in variable-speed dynamics, sampling rate inconsistencies, and complex motion patterns. Frequency-domain methods like FFT and wavelet transforms detect oscillatory behaviors to improve motion analysis reliability. The study uses spectral analysis and time–frequency domain techniques to detect motion inconsistencies that may cause mechanical wear, instability, or energy waste. Crest factor analysis and phase relationship assessment can also detect misalignment, structural resonance, and transient perturbations that conventional metrics miss. Full article

To address the dynamic characteristics of vehicle semi-active suspension systems under special operating conditions and multi-source excitations, this paper proposes a fuzzy adaptive proportional–integral–derivative model predictive control (PID-MPC) strategy aimed at enhancing ride comfort during vehicle operation. The proposed approach employs MPC as the primary controller to optimize suspension performance, incorporating a fuzzy adaptive PID compensation mechanism for real-time adjustment of PID parameters, thereby improving control efficacy. A half-car semi-active suspension model was established on the MATLAB/Simulink (2020b) platform, with simulation validation conducted across diverse road profiles, including speed bump road surface, Class B road surface, and Class C road surface. Simulation results demonstrate that the proposed strategy achieves a significant reduction in both vehicle vertical acceleration and vehicle pitch angle acceleration while maintaining appropriate suspension deflection and tire dynamic loads, effectively elevating occupant ride comfort. Research demonstrates that the fuzzy adaptive PID-MPC control strategy exhibits commendable performance under typical road operating conditions, possessing notable potential for practical engineering implementation. Full article

In modern power systems, FACTS tools are essential for addressing voltage variation along with fault ride-through (FRT) challenges within the electrical power systems, particularly for wind generation integration. Several prominent publications emphasize that the squirrel cage induction generator (SCIG) currently comprises about 15% of operational wind turbines. This research proposes the use of FACTS devices to boost voltage stability and FRT capability. The implementation of these devices leads to improved efficiency in the electrical power system. This study considers many events, including an ideal wind profile, turbulent wind profile, symmetrical faults, and unsymmetrical faults, to support the proposed selection. Furthermore, the proposed approach is evaluated by comparison between a fixed capacitor, static synchronous compensator (STATCOM), and Static VAR Compensator (SVC) to guarantee the achievement of voltage stability, reactive power consumption, and FRT capacity under various wind speed profiles and fault conditions. An overall evaluation is conducted to compare them in all examined circumstances and to highlight their advantages and effects. The simulation findings demonstrate the efficacy and primacy of FACTS in enhancing the functioning of an integrated wind system, which is built upon a grid-connected SCIG, as well as enhancing the power system performance. The MATLAB/Simulink toolbox is used to design the models of SCIG, SVC, and STATCOM. Full article

This study investigated the cognitive profiles of Italian university students with dyslexia using the WAIS-IV, comparing them to peers without specific learning disorders. Seventy-one participants took part: 36 with a diagnosis of dyslexia and 35 matched controls. While dyslexic adults showed lower Full Scale IQ (FSIQ) scores compared to controls, their scores remained within the average range. They showed deficits in Working Memory Index (WMI) and Processing Speed Index (PSI) but performed similarly to controls in Verbal Comprehension Index (VCI) and Perceptual Reasoning Index (PRI). Significant group differences also emerged in Arithmetic Reasoning, Symbol Search, and Coding subtests. Logistic regression identified WMI and PSI as the most reliable predictors of dyslexia, showing a good predictive value in discriminating between adults with and without dyslexia. Additionally, dyslexic adults displayed lower Cognitive Proficiency Index (CPI) scores relative to their General Ability Index (GAI), and lower FSIQ scores compared to controls. Overall, dyslexic adults exhibit a distinctive cognitive profile with strengths and weaknesses. This pattern can aid in dyslexia diagnosis, particularly in individuals who have compensated through extensive reading experience in a highly regular orthography. Full article

Defects arising from the 3D printing process of continuous fiber-reinforced thermoplastic composites primarily hinder their overall performance. These defects particularly include twisting, folding, and breakage of the fiber bundle, which are induced by printing trajectory errors. This study presents a follow-up theory assumption to address such issues, elucidates the formation mechanism of printing trajectory errors, and examines the impact of key geometric parameters—trace curvature, nozzle diameter, and fiber bundle diameter—on these errors. An error model for printing trajectory is established, accompanied by the proposal of a trajectory error compensation method premised on maximum printable curvature. The presented case study uses CCFRF/PA as an exemplar; here, the printing layer height is 0.1~0.3 mm, the fiber bundle radius is 0.2 mm, and the printing speed is 600 mm/min. The maximum printing curvature, gauged by the printing trajectory of a clothoid, is found to be 0.416 mm⁻¹. Experimental results demonstrate that the error model provides accurate predictions of the printed trajectory error, particularly when the printed trajectory forms an obtuse angle. The average prediction deviations for line profile, deviation kurtosis, and deviation area ratio are 36.029%, 47.238%, and 2.045%, respectively. The error compensation effectively mitigates the defects of fiber bundle folding and twisting, while maintaining the printing trajectory error within minimal range. These results indicate that the proposed method substantially enhances the internal defects of 3D printed components and may potentially be applied to other continuous fiber printing types. Full article

Recently, terahertz (THz) radar has been widely researched for its high-resolution in space target imaging. Due to the high rendezvous speed and the short wavelength of THz radar, the traditional stop-and-go model, along with its supporting algorithms, is not applicable. Therefore, a method that jointly compensates the intra- and inter- pulse errors of space targets’ echo is proposed. The algorithm includes the following steps: firstly, a coarse estimation of targets’ translational velocity at part of pulses is conducted through Fractional Fourier transform (FrFT). Then, the improved least square fitting (ILSF) is employed to parameterize the velocity–time dependency of the target. Furthermore, the concept of synthetic waveform entropy (SWE) of a one-dimensional range profile is put forward as the accuracy metric of envelope alignment. Finally, with SWE serving as the fitness function, the Grey Wolf Optimizer (GWO) algorithm is used to search for optimal estimated translation parameters. After several iterations, a fine-grained estimation of target motion parameters is achieved, while simultaneously accomplishing precise joint compensation for intra-pulse and inter-pulse errors. The validity of the proposed method is verified by numerical simulation, electromagnetic calculation data, and field-measured data. Full article

Future aircraft designs with a wide range of performance parameters, such as electric and supersonic aircraft, will have to be accommodated in traditional airspace designs in the future. Allowing an individual optimization of traditional approach speed profiles has a similar, broadening effect on approach speed characteristics. The resulting necessity of integrating Increasing Diverse Operations (IDO) will lead to a reduction in capacity at hub airports, as larger gaps will have to be inserted between aircraft with very different speed profiles. This is due to the large range of different approach speeds that IDO encompasses. Such a development will present a challenge for airports, which are already operating at or near their capacity limit. An alternative routing towards an intercept point at a late stage of the final approach can provide two approach options with low interference for subsequent traffic. Based on traffic data from London Heathrow, this study evaluates the performance in terms of runway capacity for different constellations of this procedure. Moreover, the biphasic evaluation, conducted through theoretical calculations for a constant separation distance and a fast-time simulation for a constant separation time, yielded key findings that facilitated the development of an optimized procedure for a traffic mix with significant speed differences to compensate IDO-related capacity losses as far as possible. Full article

Climate constraints impose greenhouse gas emissions mitigation, and passenger cars have considerable contributions to contribute to this. To improve the engine efficiency of vehicles equipped with conventional powertrains, many technologies are available but with limited individual contribution. The experimental assessment of some technology regarding fuel economy measurement results is sometimes lower than test uncertainties. This study proposes a methodology to compensate the fuel economy for two test uncertainties: vehicle speed variations and battery recharging. The proposed method can be applied when investigating the effects of different vehicle design changes, including engine power cell design. In this work, the proposed method is demonstrated on the test of two oils: one 5W40, the other 5W20, both without FM. Applying the proposed methodology to experimental results, the expected higher influence of oil viscosity on urban conditions could be observed, and the experimental results presented a much better correlation with the vehicle numerical simulation. Applying the proposed compensation, fuel savings of using the 5W20 in comparison to the 5W40 oil was 3.5% under urban conditions and 2.0% on highways. Full article

The rapid and accurate reconstruction of the high-resolution range profiles (HRRPs) of high-speed targets from incomplete wideband radar echoes is a critical component in space target recognition tasks (STRTs). However, state-of-the-art HRRP reconstruction algorithms based on sparse Bayesian learning (SBL) are computationally expensive and require the manual selection of prior scale parameters. To address these challenges, this paper proposes a model-driven deep network based on fast mean-field SBL (FMFSBL-Net) for the HRRP reconstruction of high-speed targets under missing data conditions. Specifically, we integrate a precise velocity compensation and HRRP reconstruction into the mean-field SBL framework, which introduces a unified SBL objective function and a mean-field variational family to avoid matrix inversion operations. To reduce the performance loss caused by mismatched prior scale parameters, we unfold the limited FMFSBL iterative process into a deep network, learning the optimal global prior scale parameters through training. Additionally, we introduce a sparsity-enhanced loss function to improve the quality and noise robustness of HRRPs. In addition, simulation and measurement experimental results show that the proposed FMFSBL-Net has a superior reconstruction performance and computational efficiency compared to FMFSBL and existing state-of-the-art SBL framework type algorithms. Full article

This paper presents the design and performance evaluation of an experimental platform that emulates the static and dynamic behavior of a 3 kW Wind Energy Conversion System (WECS). The platform includes a wind turbine emulator (WTE) using a separately excited DC motor (SEDCM) as the prime mover, coupled with a grid-connected doubly-fed induction generator (DFIG). This setup enables comprehensive laboratory studies of a WECS without the need for large-scale field installations. A novel inertia compensation strategy is implemented to ensure the SEDCM accurately replicates the power and torque characteristics of a real wind turbine across various wind profiles. The DFIG was chosen for its high efficiency at variable wind speeds and its reduced power converter requirements compared to other generators. The control strategy for the DFIG is detailed, highlighting its performance and seamless integration within the system. Unlike most studies focusing on generators connected to simple loads, this research considers a grid-connected system, which introduces additional challenges and requirements. This study thoroughly investigates the grid-connected converter, addressing specific demands for grid connection and ensuring compliance with grid standards. Experimental results validate the effectiveness of the emulator, demonstrating its potential as a key tool for optimizing wind turbine control strategies and real-time algorithm validation, and enhancing the performance and reliability of renewable energy systems. Full article