Search Results (245)

This paper presents an accurate analysis of the power losses of an interior permanent magnet synchronous motor fed by a cascaded H-bridge multilevel inverter. The main goal of this study is to investigate the impact of the cascaded h-bridge inverter, multicarrier PWM strategies, and inverter switching frequency on the synchronous motor power losses. With this aim in mind, a detailed frequency domain power analysis was carried out on motor power losses at different operating points in the frequency–torque plane. Motor power losses were further categorized into fundamental and harmonic power losses. This evaluation involved driving the power converter using six distinct multicarrier PWM strategies at four different switching frequencies. Additionally, a comparison was conducted with a conventional two-level PWM inverter to quantify the reduction in motor power losses. The experimental results show that the cascaded h-bridge inverter guarantees a notable increase in the motor efficiency, up to 7%, and losses in segregation at the fundamental frequency, if compared to the standard two-level PWM inverter, especially at low speed and with partial-load conditions. Such results mark out the cascaded H-bridge inverter as a valuable choice, also with regard to low-voltage drive applications. Full article

A novel discrete-time internal model control (IMC) method cascaded with a discrete-time equal-order fractional Butterworth (EFBW) filter is proposed for multivariable systems with time-delay and non-minimum-phase (NMP) zeros. This is the first attempt to design such a control scheme in the discrete-time domain, as previous work has typically focused on continuous-time systems. An inverted decoupling (ID) method is introduced and integrated with the discrete-time IMC controller, forming a discrete-time ID-IMC scheme that mitigates coupling effects among control loops. Additionally, a discrete-time EFBW filter is designed to balance flexibility and design complexity effectively, with technical specifications guiding the determination of the filter’s optimal order. Structured singular value analysis is conducted to guarantee the stability and robustness of the resulting closed-loop system. Illustrative examples are provided, demonstrating the effectiveness and advantages of the proposed control method. Full article

This study introduces a novel control strategy tailored to nonlinear systems with non-minimum phase (NMP) characteristics. The framework leverages reinforcement learning within a cascade control architecture that integrates an Actor–Critic structure. Controlling NMP systems poses significant challenges due to the inherent instability of their internal dynamics, which hinders effective output tracking. To address this, the system is reformulated using the Byrnes–Isidori normal form, allowing the decoupling of the input–output pathway from the internal system behavior. The proposed control architecture consists of two nested loops: an inner loop that applies input–output feedback linearization to ensure accurate tracking performance, and an outer loop that constructs reference signals to stabilize the internal dynamics. A key innovation in this design lies in the incorporation of symmetry principles observed in both system behavior and control objectives. By identifying and utilizing these symmetrical structures, the learning algorithm can be guided toward more efficient and generalized policy solutions, enhancing robustness. Rather than relying on classical static optimization techniques, the method employs a learning-based strategy inspired by previous gradient-based approaches. In this setup, the Actor—modeled as a multilayer perceptron (MLP)—learns a time-varying control policy for generating intermediate reference signals, while the Critic evaluates the policy’s performance using Temporal Difference (TD) learning. The proposed methodology is validated through simulations on the well-known Inverted Pendulum system. The results demonstrate significant improvements in tracking accuracy, smoother control signals, and enhanced internal stability compared to conventional methods. These findings highlight the potential of Actor–Critic reinforcement learning, especially when symmetry is exploited, to enable intelligent and adaptive control of complex nonlinear systems. Full article

In the last decade, countries have experienced increased solar radiation, leading to an increase in the use of solar photovoltaic (PV) systems to boost renewable energy generation. However, the high solar penetration into these systems can disrupt the normal operation of the distribution grid. Thus, a major concern is the impact of these units on power quality indices. To improve these units, one approach is to design more efficient power inverters. This study introduces a pulse width modulation (PWM) technique for multilevel power inverters, employing a sine wave as the carrier wave and an amplitude over-modulated triangular wave as the modulator (PSTM-PWM). The proposed technique improves the waveform quality and increases the AC voltage output of the multilevel inverter compared with that from conventional PWM techniques. In addition, it ensures compliance with the EN50160 standard. These improvements are achieved with a lower modulation order than that used in traditional techniques, resulting in reduced losses in multilevel power inverters. The proposed approach is then implemented using a five-level cascaded H-bridge inverter. In addition, a comparative analysis of the efficiency of multilevel power inverters was performed, contrasting classical modulation techniques with the proposed approach for various modulation orders. The results demonstrate a significant improvement in both total harmonic distortion (THD) and power inverter efficiency. Full article

Multilevel inverters (MLIs) have become fundamental in contemporary power electronics, providing enhanced performance compared to conventional two-level inverters regarding their output voltage quality, efficiency, and scalability. This study comprehensively assesses multilevel inverter technologies, including their topologies, control systems, and various applications. The study starts with a comprehensive examination of the core concepts of MLIs, subsequently embarking on a detailed evaluation of both conventional and innovative topologies, such as diode-clamped, flying capacitor, cascaded H-bridge, and modular multilevel converters. The study further examines the control systems used in MLIs, including Pulse Width Modulation (PWM), space vector modulation (SVM), and Model Predictive Control (MPC), emphasizing their benefits and drawbacks. The applications of MLIs in renewable energy systems, electric cars, industrial drives, and grid integration are comprehensively examined. The study closes by examining growing trends, difficulties, and future research paths, emphasizing the ability of MLIs to transform power conversion systems. Full article

Cross-modal image registration for unmanned aerial vehicle (UAV) platforms presents significant challenges due to large-scale deformations, distinct imaging mechanisms, and pronounced modality discrepancies. This paper proposes a novel multi-scale cascaded registration network based on style transfer that achieves superior performance: up to 67% reduction in mean squared error (from 0.0106 to 0.0068), 9.27% enhancement in normalized cross-correlation, 26% improvement in local normalized cross-correlation, and 8% increase in mutual information compared to state-of-the-art methods. The architecture integrates a cross-modal style transfer network (CSTNet) that transforms visible images into pseudo-infrared representations to unify modality characteristics, and a multi-scale cascaded registration network (MCRNet) that performs progressive spatial alignment across multiple resolution scales using diffeomorphic deformation modeling to ensure smooth and invertible transformations. A self-supervised learning paradigm based on image reconstruction eliminates reliance on manually annotated data while maintaining registration accuracy through synthetic deformation generation. Extensive experiments on the LLVIP dataset demonstrate the method’s robustness under challenging conditions involving large-scale transformations, with ablation studies confirming that style transfer contributes 28% MSE improvement and diffeomorphic registration prevents 10.6% performance degradation. The proposed approach provides a robust solution for cross-modal image registration in dynamic UAV environments, offering significant implications for downstream applications such as target detection, tracking, and surveillance. Full article

Traditional multilevel inverter topologies, such FC, NPC, and CHB, have a few significant disadvantages. They need a great number of parts, which raises the complexity, expense, and switching losses. Furthermore, their intricate control schemes make voltage balancing and synchronization challenging. Lastly, under some circumstances, they experience severe harmonic distortion, necessitating the inclusion of expensive filters to enhance signal quality. This paper proposes a novel multilevel converter topology that uses the phase-disposition PWM (PD-PWM) technique to control a 19-level output. This new configuration maintains performance comparable to the CHB-MLI reference while using fewer switches, simplifying control, and reducing costs. Our approach is based on extensive simulations conducted in the MATLAB Simulink environment, with results compared to the CHB-MLI. A low-pass filter is added to improve the output voltage quality, reducing the THD% to 1.33%. This strategy offers several advantages, including simpler control, lower costs, increased reliability, and higher-quality output. The system was replicated using MATLAB Simulink and validated through hardware-in-the-loop (HIL) testing. The HIL method ensures real-world testing without causing damage to the hardware. The integrated system includes sensors and necessary hardware for a comprehensive energy management solution. Full article

The conventional power distributions methods face many challenges, such as high switching frequency, multiple carrier cycles, and single power distribution. To address the above issues, a novel power distribution based on the selective harmonic elimination (PD–SHE) strategy is proposed to achieve arbitrary power distribution and selective harmonic elimination but with low switching frequency and single carrier cycle. Firstly, the novel PD–SHE model is established based on the principles of SHE and power calculation theory, where distribution ratio is introduced to adjust power distribution arbitrarily and its constraints have been deduced. In addition, the issue of redundancy of solution is also analyzed and solved by adding valid constraints. Finally, polynomial homotopy continuation (PHC) algorithm is applied to solve the novel PD–SHE model. Then, all the physically realizable solutions can be found without choosing the initial value in the full range of modulation index. The results of simulation analysis show the effectiveness of PD–SHE strategy and the superiority of PHC algorithm in solving the global optimal solution. Moreover, the reliability of the global optimal solution for PD–SHE strategy is verified via physical experiments in terms of harmonic elimination and active power distribution. Full article

As one of the world’s economically valuable fruit crops, citrus has its quality and productivity closely tied to the degree of fruit ripeness. However, accurately and efficiently detecting citrus ripeness in complex orchard environments for selective robotic harvesting remains a challenge. To address this, we constructed a citrus ripeness detection dataset under complex orchard conditions, proposed a lightweight algorithm based on visual saliency priors and the RT-DETR model, and named it LightSal-RTDETR. To reduce computational overhead, we designed the E-CSPPC module, which efficiently combines cross-stage partial networks with gated and partial convolutions, combined with cascaded group attention (CGA) and inverted residual mobile block (iRMB), which minimizes model complexity and computational demand and simultaneously strengthens the model’s capacity for feature representation. Additionally, the Inner-SIoU loss function was employed for bounding box regression, while a weight initialization method based on visual saliency maps was proposed. Experiments on our dataset show that LightSal-RTDETR achieves a mAP@50 of 81%, improving by 1.9% over the original model while reducing parameters by 28.1% and computational cost by 26.5%. Therefore, LightSal-RTDETR effectively solves the citrus ripeness detection problem in orchard scenes with high complexity, offering an efficient solution for smart agriculture applications. Full article

In complex orchard environments, rapidly and accurately identifying pomegranate fruits at various growth stages remains a significant challenge. Therefore, we propose YOLO-MSNet, a lightweight and enhanced pomegranate fruit detection model developed using YOLOv11. Firstly, the C3k2_UIB module is elegantly designed by integrating the Universal Inverted Bottleneck (UIB) structure into the model, while convolutional modules within the model are seamlessly replaced by AKConv units, thereby markedly reducing the overall complexity of the model. Subsequently, a novel parallel cascaded attention module called SSAM is designed as a way to improve the model’s ability to clearly see small details of the fruit against the background of a complex orchard. Additionally, a Dynamic Adaptive Bidirectional Feature Pyramid Network (DA-BiFPN) that employs adaptive sampling strategies to optimize multi-scale feature fusion is designed. The C3k2_UIB module complements this by reinforcing feature interactions and information aggregation across various scales, thereby enhancing the model’s perception of multi-scale objects. Furthermore, integrating VFLoss and ShapeIOU further refines the model’s ability to distinguish between overlapping and differently sized targets. Finally, comparative evaluations conducted on a publicly available pomegranate fruit dataset against state-of-the-art models demonstrate that YOLO-MSNet achieves a 1.7% increase in mAP50, a 21.5% reduction in parameter count, and a 21.8% decrease in model size. Further comparisons with mainstream YOLO models confirm that YOLO-MSNet has a superior detection accuracy despite being significantly lighter, making it especially suitable for deployment in resource-constrained edge devices, effectively addressing real-world requirements for fruit detection in complex orchard environments. Full article

Acute erythroid leukemia (AEL) is a rare and aggressive hematological malignancy managed with chemotherapy, targeted therapies, and stem cell transplantation. However, these treatments often suffer from limitations such as refractoriness, high toxicity, recurrence, and drug resistance, underscoring the urgent need for novel therapeutic approaches. Dibromo-edaravone (D-EDA) is a synthetic derivative of edaravone (EDA) with unreported anti-leukemic properties. In this study, D-EDA demonstrated potent cytotoxicity against HEL cells with an IC₅₀ value of 8.17 ± 0.43 μM using an MTT assay. Morphological analysis via inverted microscopy revealed reductions in cell number and signs of cellular crumpling and fragmentation. Flow cytometry analysis, Hoechst 33258 staining, Giemsa staining, a JC-1 assay, and a reactive oxygen species (ROS) assay showed that D-EDA induced apoptosis in HEL cells. Furthermore, D-EDA induced S-phase cell cycle arrest. Western blot analysis showed significant upregulation of key apoptosis-related proteins, including cleaved caspase-9, cleaved caspase-3, and cleaved poly ADP-ribose polymerase (PARP), alongside a reduction in Bcl-2 expression. Additionally, oncogenic markers such as c-Myc, CyclinA2, and CDK2 were downregulated, while the cell cycle inhibitor p21 was upregulated. Mechanistic studies involving molecular docking, a cellular thermal shift assay (CETSA), the caspase inhibitor Z-VAD-FMK, JAK2 inhibitor Ruxolitinib, and STAT3 inhibitor Stattic revealed that D-EDA activates the caspase cascade and inhibits the JAK2-STAT3 signaling pathway in HEL cells. In vivo, D-EDA improved spleen structure, increased the hemolysis ratio, and extended survival in a mouse model of acute erythroleukemia. In conclusion, D-EDA induces apoptosis via the caspase cascade and JAK2-STAT3 signaling pathway, demonstrating significant anti-leukemia effects in vitro and in vivo. Thus, D-EDA may be developed as a potential therapeutic agent for acute erythroleukemia. Full article

Numerous cascaded inverter configurations have been developed to generate higher voltage levels, thereby improving performance and lowering costs. Comparing conventional delta-connected cascaded H-bridge (CHB) multilevel inverters to star-connected CHB multilevel inverters reveals a disadvantage. In conventional delta-connected CHB multilevel inverters, more switches are unavoidably needed to achieve the same line-to-line grid voltage, since more H-bridges cascaded in series are required than in a star-connected CHB. This paper presents a modified topology based on the delta-connected CHB multilevel configuration to provide the same number of line-to-line voltage levels as a star-connected CHB, using an equivalent number of switches. The number of switches in the proposed multilevel inverter is decreased compared to conventional delta-connected CHB MLIs at the same voltage levels. The mathematical modeling of the proposed topology and the simulation results using a fixed load and a PV-grid connection are provided to validate the efficacy and dependability of the proposed topology. To validate the usefulness of the proposed configuration, it was practically implemented in the laboratory. Data acquisition and generation of gating signals to fire the switches were implemented using a MicroLabBox real-time controller. The prototype was examined under a resistive–inductive load and tested under different modulation indices. To demonstrate the effectiveness and the functionality of the topology, the experimental results are also provided. Full article

This paper deals with the design and control of an enhanced grid-tied photovoltaic (PV) cascaded H-Bridge (CHB) inverter, which suffers from issues related to operation in the overmodulation region in the case of a deep mismatch configuration of PV generators (PVGs). This can lead to reduced system performance in terms of maximum power point tracking (MPPT) efficiency, or even instability (i.e., a lack of control action). The proposed solution is to insert into the cascade a power cell fed by a battery energy storage system (BESS) with the aim of providing an additional power contribution. The latter is useful to reduce the modulation index of the cell, delivering more power than the others when a preset threshold is crossed. Moreover, a suitable hybrid modulation method is used to achieve the desired result. A simulated performance in a PLECS environment proves the viability of the proposed solution and the effectiveness of the adopted control strategy. Full article

Grid-connected single-phase inverters require accurate phase detection for synchronization and power control. Traditionally, phase-locked loops (PLLs) are used to estimate grid parameters. This paper proposes a novel approach that determines the grid phase angle using only current feedback, eliminating the need for grid voltage measurements or cascaded control schemes. The proposed method integrates a phase angle observer with a current controller to regulate real and reactive power. Lyapunov stability analysis and hardware experiments validate the effectiveness of the approach. Full article

The growing demand for higher reliability and efficiency in modern electric drives, coupled with the increasing adoption of multi-phase machines, has necessitated advancements in fault-tolerant control strategies. This paper presents a fault tolerance analysis for a six-phase permanent magnet synchronous machine (PMSM) connected to a five-level cascaded H-bridge converter, employing a level-shift pulse width modulation (LSPWM) technique. Unlike existing strategies, this work integrates a unique combination of three key innovations: first, a fault detection mechanism capable of identifying faults in both machine phases and inverter legs with high precision; second, an open-circuit fault compensation strategy that dynamically reconfigures the faulty inverter phase leg into a two-level topology to reduce losses and preserve healthy switches; and third, a modified closed-loop control method designed specifically to mitigate the adverse effects of short-circuit faults while maintaining system stability. The proposed approach is validated through rigorous simulations in Simulink and Hardware-in-the-Loop (HIL) tests, demonstrating its robustness and applicability in high-reliability applications. Full article