Arabian Journal for Science and Engineering最新文献

{"title":"A Multi-head Attention Transformer with Convolutional Projections for Skin Cancer Image Classification","authors":"Marwa Kahia,&nbsp;Bassem Bsir,&nbsp;Fathi Kallel","doi":"10.1007/s13369-026-11416-6","DOIUrl":"10.1007/s13369-026-11416-6","url":null,"abstract":"<div><p>Skin cancer detection is a crucial task in dermatology, with accurate classification of skin lesions playing a key role in improving patient outcomes. This paper proposes a modified architecture based on Modified Multi-Head Attention Transformer (MMHAT) for skin image classification, specifically targeting the detection of malignant melanoma and melanocytic nevus. In this work, we introduce a hybrid approach that integrates convolutions with linear projections, combining the ability of convolutions to effectively capture local spatial features with the capacity of linear projections to model global relationships. This adaptive mechanism enhances the model’s ability to extract both fine-grained and large-scale patterns, leading to a more expressive and robust feature representation. Additionally, we incorporate a ReLU activation function in the adaptive weighting mechanism to ensure that only positive contributions from different components are retained. The hybrid approach is evaluated on the publicly available ISIC 2018 dataset, containing a diverse range of dermoscopic images. Experimental results show that the proposed Transformer model achieves an accuracy of 0.91, outperforming conventional models such as ResNet-50 and InceptionV3, which achieved accuracy of 0.90 and 0.85, respectively. Furthermore, experiments with and without multi-head attention demonstrate the significant impact of the attention mechanism in improving model performance, particularly in skin cancer detection.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 15","pages":"18645 - 18661"},"PeriodicalIF":3.1,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148811097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amine-Aniline Terminated Copolymerization of Fibrous Silica for the Extraction of Polar Phenolic Pollutants from Wastewater Using Membrane Supported Micro-SPE and the Subsequent HPLC–DAD Analysis","authors":"Shaima’ Ibrahim Alsabbahen,&nbsp;Shehzada Muhammad Sajid Jillani,&nbsp;Saheed A. Ganiyu,&nbsp;Abdulkadir Tanimu,&nbsp;Khalid Alhooshani","doi":"10.1007/s13369-026-11542-1","DOIUrl":"10.1007/s13369-026-11542-1","url":null,"abstract":"<div><p>The presence of phenols in wastewater poses significant environmental and health risks due to their toxicity and persistence. This study explores a targeted approach of amine and/or aniline functionalization of fibrous silica material for the membrane supported micro solid phase extraction of polar phenols. Therefore, four different sorbents were synthesized: unmodified fibrous silica (FS), FS functionalized with N1-(3-Trimethoxysilylpropyl) diethylenetriamine (FS-Amine), FS functionalized with N-[3-(Trimethoxysilyl)propyl] aniline (FS-Aniline), and FS copolymerized with both amine and aniline monomers (FS-Mix). The synthesized materials were characterized using XPS, XRD, FTIR, SEM, and TGA techniques to confirm their structural and functional properties. The µ-SPE method was optimized for key parameters, including sorbent dosage, extraction time, desorption conditions, and solvent composition. High-performance liquid chromatography with diode array detector (HPLC–DAD) analysis demonstrated that FS-Mix exhibited the highest extraction efficiency for five target phenols: 2,3-Dichlorophenol (2,3-DCP), 3,4-Dichlorophenol (3,4-DCP), 2,4,6-Trichlorophenol (2,4,6-TCP), 4-Bromophenol (4-BP), and 4-Nitrophenol (4-NP). Method validation showed good linearity (<i>R</i>² &gt; 0.99), low limits of detection (LOD: 0.97–2.31 ppb), and high relative recovery rates (90.60–113.60%). Real wastewater analysis confirmed the applicability of FS-Mix for phenol extraction, with detected concentrations of 1.601 µg·mL⁻¹ for 4-NP and 0.055 µg·mL⁻¹ for 4-BP. This study highlights the potential of functionalized fibrous silica as a highly effective and selective sorbent for µ-SPE, offering a promising approach for the environmental monitoring and removal of phenols from wastewater.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 17","pages":"20271 - 20283"},"PeriodicalIF":3.1,"publicationDate":"2026-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148987039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale","authors":"Sameha Alshakhsi,&nbsp;Ala Yankouskaya,&nbsp;Magnus Liebherr,&nbsp;Raian Ali","doi":"10.1007/s13369-026-11386-9","DOIUrl":"10.1007/s13369-026-11386-9","url":null,"abstract":"<div><p>There is an urgent need for reliable, culturally validated instruments to assess psychological responses to AI in general and large language models (LLMs). This need is global issue, but it is especially urgent among Arabic-speaking populations, where AI and LLMs adoption is accelerating, yet psychometric tools remain limited. This study presents the first validation of the LLM-D12, a dual-dimensional scale assessing Instrumental and Relationship Dependency on LLMs, in an Arab sample. A total of 250 Arab participants completed the Arabic version of the LLM-D12. Confirmatory Factor Analysis confirms the original 2-factor structure of LLM-D12 with all items showing good loading of corresponding Instrumental and Relationship Dependency. The scale showed good to excellent internal reliability (Cronbach alpha is 0.90 for Total, 0.85 for Instrumental Dependency, and 0.90 for Relationship Dependency). External validation revealed that Instrumental Dependency was positively associated with AI acceptance and internet addiction, while Relationship Dependency was linked to lower need for cognition and greater trustworthiness of LLM, demonstrating sensitivity of this instrument to different use and personal factors. These findings confirm that Arabic LLM-D12 is a psychometrically sound, culturally appropriate instrument, offering a necessary tool for research, education, and policy concerning AI and LLMs engagement in Arab contexts.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 15","pages":"18621 - 18644"},"PeriodicalIF":3.1,"publicationDate":"2026-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13369-026-11386-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148811028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual Duty Cycle Optimal Model Predictive Control for Permanent Magnet Hub Motors with Torque-Flux Linkage Decoupling","authors":"Li Quan,&nbsp;Xiongwei Xia,&nbsp;Xiaoyong Zhu,&nbsp;Chao Zhang","doi":"10.1007/s13369-026-11407-7","DOIUrl":"10.1007/s13369-026-11407-7","url":null,"abstract":"<div><p>A dual duty cycle optimal model predictive control (DDCO-MPC) strategy is proposed to decouple torque and flux linkage in cost function, which achieve flux linkage and torque optimization without weighting factors. In this strategy, the change rate models of torque and flux linkage are constructed, and the corresponding cost functions are set to obtain the voltage vectors <i>V</i>_T, <i>V</i>_f and their duty cycles <i>d</i>_T and <i>d</i>_f, respectively. Duty cycle is dynamically assigned through a predictive cross-correction framework between torque and flux linkage, balancing the optimization of multi-objective operations and significantly improving control performance. Meanwhile, an adaptive compensation mechanism is integrated with the vector state evaluation algorithm to dynamically adjust duty cycles, achieving optimal trade-offs between transient response and steady-state error suppression. This synergistic approach enhances both rapid torque response and high-fidelity flux linkage tracking, thereby elevating the dynamic performance of hub motors under transient and steady-state conditions. In addition, the dynamic constraint d<i>i</i>_d/dt = 0 is introduced on the basis of the traditional <i>i</i>_d = 0 strategy, which can not only suppress the <i>d</i>-axis perturbation, stabilize the flux linkage phase, and reduce the torque ripple, but also improve the <i>q</i>-axis current utilization and optimize the torque output efficiency. Simulations and experiments verify the correctness and effectiveness of the control method.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 16","pages":"19643 - 19655"},"PeriodicalIF":3.1,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148816197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Indirect-Relay Autotuning: A Model-Free Approach to Robust PID Controller Design and Implementation","authors":"Dhiraj Shrivastava,&nbsp;Bharat Verma,&nbsp;Akash Gupta,&nbsp;Prabin Kumar Padhy,&nbsp;Anupam Kumar","doi":"10.1007/s13369-026-11418-4","DOIUrl":"10.1007/s13369-026-11418-4","url":null,"abstract":"<div><p>Model-free design approaches are favoured for controller design when dealing with complex process models or models that lack accurate mathematical representation. This article presents a relay autotuning method for the PID controller for stable processes. By conducting a single ideal relay test, a limit cycle output is generated to aid in the Proportional–Integral–Derivative (PID) controller design. The design process involves two steps: initially, a zero-phase PID controller is derived to ensure a minimum gain margin; subsequently, the phase margin criterion is achieved using the indirect design method (IDA2). The proposed IDA2-relay autotuning method enables users to design a PID controller and adjust its robustness using a single tunable variable, which exhibits a monotonic relationship with robustness. The efficacy of the IDA2-<i>relay</i> PID autotuner is validated through two different simulations on higher-order plants. The experimental validation is also investigated for speed control of the DC motor with IDA2-relay autotuner implemented on Arduino microcontroller board. Under nominal conditions, the proposed method provides enhanced tracking and disturbance rejection, achieving up to 42% reduction in IAE and 29% in ISE compared to existing methods, while maintaining improved robustness. Similarly, in the DC motor experiment, the performance is improved by 3.13% in the presence of load changes.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 13","pages":"16365 - 16377"},"PeriodicalIF":3.1,"publicationDate":"2026-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Deep Reinforcement Learning-Based Approach for Optimal Pulse Number Selection in ISAR Imaging","authors":"Reza Mohammadi,&nbsp;Ali Jabar Rashidi","doi":"10.1007/s13369-026-11333-8","DOIUrl":"10.1007/s13369-026-11333-8","url":null,"abstract":"<div><p>Determining an appropriate Coherent Processing Interval (CPI) is a fundamental challenge in Inverse Synthetic Aperture Radar (ISAR) imaging, as it directly governs the trade-off between cross-range resolution and rotational motion–induced image blurring. Since the CPI depends on both the Pulse Repetition Interval (PRI) and the number of transmitted pulses, this paper focuses on the adaptive determination of the optimal pulse number under a fixed-PRI assumption. A Double Deep Q-Network (Double DQN) based reinforcement learning framework is proposed, in which an agent sequentially adjusts the number of pulses used for image formation in order to maximize ISAR image quality. At each time step, the agent observes the formed ISAR image, extracts discriminative features using a convolutional neural network, and selects a discrete action to increase, decrease, or maintain the current pulse number. Image quality is quantitatively defined using a sparsity-based metric, which reflects image focus and concentration of dominant scatterers, and a Gaussian-shaped reward function is designed to guide the learning process. Through this formulation, the agent implicitly balances two CPI-dependent physical effects: insufficient target rotation leading to poor cross-range resolution and excessive rotation leading to image blurring. The proposed method is evaluated using simulated ISAR data for point-scatterers-based rigid body targets with varying rotational velocities and initial pulse numbers conditions. Experimental results indicate that the trained agent reliably converges to an optimal or near-optimal number of pulses, yielding well-focused ISAR images without the need for explicit cross-range resolution enhancement or rotational motion compensation.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 16","pages":"19619 - 19642"},"PeriodicalIF":3.1,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148816309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computing a Positive Semidefinite Arrowhead Matrix Closest to Noisy Data","authors":"Suliman Al-Homidan","doi":"10.1007/s13369-026-11467-9","DOIUrl":"10.1007/s13369-026-11467-9","url":null,"abstract":"<div><p>Arrowhead matrices, consisting of a diagonal block augmented by a single dense row and column, arise naturally in a wide range of applications in numerical linear algebra, physics, statistics, optimization, and network analysis. In many of these settings, positive semidefiniteness is a fundamental requirement, for example in covariance estimation, stability analysis, and energy-based models. Motivated by these applications, we study the problem of computing the nearest positive semidefinite arrowhead matrix to a given data matrix in the Frobenius norm. The data matrix may be noisy or indefinite and is not necessarily symmetric, which presents additional challenges compared to classical nearest positive semidefinite approximation problems. We formulate the problem as a convex optimization problem with both structural and semidefiniteness constraints and investigate several solution approaches. These include an alternating projection method, semidefinite programming formulations, and mixed semidefinite–second-order cone programming formulations that explicitly exploit the arrowhead structure. By leveraging this structure, we derive reduced formulations with significantly lower computational complexity. Numerical experiments on randomly generated matrices of orders up to <span>( n=1000)</span> demonstrate that while projection-based and standard semidefinite programming methods are reliable, they become computationally expensive for large-scale problems. In contrast, the mixed second-order cone formulations exhibit excellent scalability, requiring substantially fewer iterations and dramatically reduced CPU time while maintaining comparable solution accuracy. These results highlight the effectiveness of structure-exploiting optimization formulations for large-scale nearest positive semidefinite arrowhead matrix approximation problems.\u0000</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 13","pages":"16355 - 16364"},"PeriodicalIF":3.1,"publicationDate":"2026-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Fractional-Order Proportional-Integral-Derivative Controller Tuned with Hybrid Particle Swarm Optimization-Artificial Bee Colony Algorithm for Boost Converters: An Experimental Study","authors":"Ibrahim Aliskan","doi":"10.1007/s13369-026-11423-7","DOIUrl":"10.1007/s13369-026-11423-7","url":null,"abstract":"<div><p>This paper presents Fractional-Order Proportional-Integral-Derivative (FO-PID) controllers for a voltage feedback boost converter operated in continuous conduction mode. If parameters of a classical PID controller are considered, it is seen that a FO-PID has two additional parameters to be set. Achieving optimum values for those parameters is a laborious task. Here, a hybrid optimization algorithm is developed as a serial connection of particle swarm optimization (PSO) and artificial bee colony (ABC) algorithm to tune FO-PID parameters. Handling the cost functions of integral of absolute error and integral of squared error (ISE) with PSO, ABC and hybrid algorithm, six different FO-PID controllers are achieved. Then, integer order approximates of those FO-PIDs are found, and discrete transfer functions are derived utilizing Backward Euler method. With the help of simulation results and experimental results, the performances of a PID controller and six different FO-PID controllers are examined. To evaluate controllers’ performance, simulation data and experimental data are processed and settling time, overshoot and mean squared error (MSE) performance indices are calculated. The FO-PID HYB(ISE) controller, which has been developed by using the hybrid algorithm and ISE cost function, achieved 49.4% improvement in overshoot performance indicator with regard to PI controller in the simulations, and provided 23.04% performance increase in the MSE scale compared to PID controller in the experiments. Consequently, the control performance measures validated that the FO-PID HYB(ISE) controller is superior to the others.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 16","pages":"19601 - 19618"},"PeriodicalIF":3.1,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13369-026-11423-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148816340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quality-Aware Generative Augmentation: A Comparative Framework for Few-Shot and Imbalanced Classification Tasks","authors":"Abdurrahman Öcal,&nbsp;Kazım Kılıç,&nbsp;Kenan Kılıç","doi":"10.1007/s13369-026-11464-y","DOIUrl":"10.1007/s13369-026-11464-y","url":null,"abstract":"<div><p>Deep learning-based image classification systems necessitate large and balanced datasets for robust generalization, yet real-world scarcity (few-shot) and severe class imbalance critically limit performance, particularly regarding minority classes. This study proposes a ‘Quality-Aware Generative Data Augmentation’ framework integrated with a teacher-based synthetic data filtering mechanism to address these limitations. Utilizing Projected GAN architecture, synthetic images were generated at varying convergence stages and categorized into three distinct quality levels (Sets A, B, and C) extracted from distinct temporal training snapshots (early, intermediate, and convergence stages), yielding empirical FID scores approximately 35, 25, and 10, respectively. To ensure class consistency and semantic reliability, these samples were filtered by a teacher network (ResNet50) fine-tuned exclusively on real data, utilizing a Top-N Selection (Ranking) strategy based on confidence scores. The framework was comprehensively evaluated using MobileNetV3-Large, EfficientNet-B0, and ShuffleNet architectures on two structurally contrasting datasets: the Forest Species Database (FSD) and DermaMNIST. In the FSD dataset, the EfficientNet model’s F1-score improved from 0.881 to 0.937, while the lightweight ShuffleNet achieved a significant 0.11 improvement, rising from 0.792 to 0.903. In DermaMNIST, the filtering strategy successfully mitigated false positives in minority classes, elevating the overall F1-score to 0.8338. The findings indicate that the efficacy of generative data augmentation depends on both data quantity and the generator’s convergence stage combined with the rigour of the selection mechanism. Consequently, this study provides a methodological guideline for optimizing synthetic data usage in data-scarce and imbalanced scenarios, offering a robust solution for data-constrained and lightweight deployment environments.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 15","pages":"18597 - 18619"},"PeriodicalIF":3.1,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13369-026-11464-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148811096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined Voltage and Frequency Containment of Amphibious Hybrid Power System Using FOTI-SMC","authors":"Kothalanka Kameswara Pavan Kumar,&nbsp;Dulal Chandra Das,&nbsp;Nirmala Soren","doi":"10.1007/s13369-026-11387-8","DOIUrl":"10.1007/s13369-026-11387-8","url":null,"abstract":"<div><p>This paper addresses robust combined frequency and voltage regulation in a highly nonlinear, amphibious (aquatic and terrestrial), two-area hybrid power system (AHPS). The AHPS comprises multiple sources—thermal, dish–Stirling solar thermal (DSTS), hydro, pumped hydro, and gravity hydro units—connected to a 50-Hz grid. During operation, solar radiation fluctuations and load changes lead to significant variations in key model parameters <span>(({e.g., K}_{p},{T}_{p},{T}_{sc},{T}_{rh},{T}_{w},{T}_{1},{T}_{2}))</span>, which can cause undesirable frequency and voltage deviations. To tackle this challenge, a dynamic parameter-based modelling framework is developed for the AHPS, and a new fractional-order tilt-integral sliding mode controller (FOTI-SMC) is proposed for coordinated frequency–voltage regulation. The proposed FOTI-SMC is systematically compared with five benchmark controllers—classical PID, fractional TID, FOPID, FOTID, and nonlinear FOPISMC—whose parameters are tuned using five optimization classes (evolutionary, swarm-based, physics-based, human-inspired) and the bio-inspired Tasmanian Devil Optimization (TDO) algorithm. The TDO-tuned FOTI-SMC achieves a peak overshoot of only 1.18 for frequency deviation in area-1 (∆<i>f</i>₁), significantly outperforming the GA-tuned PID. The proposed scheme also realizes faster recovery, with settling times reduced to 15.787s for ∆<i>f</i>₁ and 12.052s for ∆<i>f</i>₂, voltage deviations (∆<i>V</i>₁ &amp; ∆<i>V</i>₂), and tie-line power (∆<i>P</i>_tie). Under realistic operating scenarios involving simultaneous variations in load, solar insolation, and modelling parameters, the TDO-FOTI-SMC maintains superior robustness, restricting overshoots to 1.517 for ∆<i>f</i>₁ and 0.931 for ∆<i>f</i>₂. Real-time validation on an OPAL-RT OP4510 platform confirms that the proposed TDO-optimized FOTI-SMC offers the most effective frequency–voltage regulation and disturbance rejection among all tested configurations.</p></div>","PeriodicalId":54354,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"51 16","pages":"19565 - 19600"},"PeriodicalIF":3.1,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148816236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}