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Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company's transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty from the logistics hub to the village, the capacity of drones for transportation, and the distribution of logistics hub locations.Moreover, this paper proposes an improved particle swarm optimization (PSO) algorithm which is a diversity-based hybrid PSO (DHPSO) algorithm to solve this model. In DHPSO, the Gaussian random walk can enhance global search in the model space, while the bubble-net attacking strategy can speed convergence. Besides, Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the algorithm. DHPSO maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current model. Comparing DHPSO with other state-of-the-art intelligent algorithms, the efficiency of the scheme can be improved by 42.58%. This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO's location selection. All the results show the location of the drone logistics hub is solved by DHPSO effectively. [ABSTRACT FROM AUTHOR]

SiC reinforced aluminum matrix composites are widely used in aerospace, electronic packaging and transportation due to their high specific strength, high thermal conductivity and high wear resistance. In this paper, SiC particle reinforced aluminum matrix composites were prepared by hot pressing sintering. The effects of SiC content on the microstructure and mechanical properties of aluminum matrix composites were studied. The phase composition, apparent density and mechanical properties of the samples were determined by X-ray diffraction, Archimedes drainage method, Rockwell hardness analysis and three-point bending method. The microstructure of the samples was analyzed by SEM. The thermal conductivity was measured by laser flash method. The results show that the hardness of the samples increases first and then decreases with the increase of the volume fraction of SiC particles from 0% to 60%, and reaches the maximum value of 90 HRB when the volume fraction of SiC is 50%. The thermal conductivity of the samples increases first and then decreases, and reaches the maximum value of 324.05 W/(m ⋅ K) when the volume fraction of SiC is 30%. With the increase of SiC volume fraction, the metal matrix and the reinforcement are closely combined without obvious pores. When the volume fraction of SiC increases to 60%, the porosity of the samples increases, the consistency decreases, and the strength decreases. [ABSTRACT FROM AUTHOR]

Over the past decade, significant research has focused on detecting abnormalities in metal laser powder bed fusion (L-PBF) additive manufacturing. Effective online monitoring systems are crucial for enhancing process stability, repeatability, and the quality of final components. Therefore, the development of in situ detection mechanisms has become essential for metal L-PBF systems, making efficient closed-loop control strategies to adjust process parameters in real time vital. This paper presents an overview of current in situ monitoring systems used in metal L-PBF, complemented by ex situ characterizations. It discusses in situ techniques employed in L-PBF and evaluates the applicability of commercial systems. The review covers optical, thermal, acoustic, and X-ray in situ methods, along with destructive and non-destructive ex situ methods like optical, Archimedes, and X-ray characterization techniques. Each technique is analyzed based on the sensor used for defect detection and the type or size of defects. Optical in situ monitoring primarily identifies large defects from powder bed abnormalities, while thermal methods detect defects as small as 100 µm and keyholes. Thermal in situ detection techniques are notable for their applicability to commercial devices and efficacy in detecting subsurface defects. Computed tomography scanning excels in locating porosity in 3D space with high accuracy. This study also explores the advantages of multi-sensor in situ techniques, such as combining optical and thermal sensors, and concludes by addressing current research needs and potential applications of multi-sensor systems. [ABSTRACT FROM AUTHOR]

Contemporary erasure poetry and the poetics of remediated forms are often taken as serving as political battlegrounds and sites of epistemic transference. At the same time, what is missing from the literature is a discussion of medieval manuscripts and the history of palimpsests. This paper explores two topics: (1) how the Archimedes palimpsest allows us to understand blackout poems as sites of knowledge production as well as conversations between polemic positions and (2) how poetic remediation can inform our valuation of the erasures situated in the Archimedes palimpsest. Through analysis of Travis Macdonald's The O Mission Repo, Rachel Stempel's "Natal Girl (& Other Repeat Offenses)," Molly R. Sullivan's "Levonorgestrel," and the Archimedes palimpsest, this paper explores how both medieval manuscripts and modern forms of poetry serve us as classroom realia, illustrating that their value extends beyond disciplinary boundaries to reveal new ways of conceiving artistic and pedagogical praxes. [ABSTRACT FROM AUTHOR]

The rapid growth of smart cities and industry causes an increase in waste production. The amount of municipal solid waste (MSW) increases by several factors, including population growth, economic status, and consumption trends. The inadequacy of basic trash data is a major issue for managing MSW. Numerous existing models based on solid waste prediction have been presented so far, but none of them predict solid waste accurately and also it consumes more time. To address these concerns, a deep convolutional spiking neural network for solid waste prediction (DCSNN-SWP) is proposed in this paper. Here, the real-time solid waste prediction data are gathered from the quantity of municipal corporation of Chennai (MCC), landfill, garden garbage, and coconut shell reports in Tamil Nadu (Chennai), such as Zone 9 (Nungambakkam), Zone 10 (Kodambakkam) and Zone 13 (Adyar). Then the collected solid waste data are pre-processed using the kernel correlation model. Then the pre-processing data is given to DCSNN-hybrid BCMO and Archimedes optimization algorithm which accurately predicts the solid waste as wet waste, dry waste, horticulture waste, and dumping yard for 2022-2032 years. The proposed DCSNN-SWP method has been implemented in Python. [ABSTRACT FROM AUTHOR]

In the 3rd century B.C.E., Archimedes wrote his treatise on the quadrature of the parabola, in which he laid out his solution to the problem of finding the area of a parabolic segment. Archimedes attacks the problem from two sides; first, he uses classical mechanics to derive an area formula, and then he uses pure geometry to prove his formula is correct. In this paper, we will present two modern approaches to this problem using calculus. The first approach can be presented to a calculus class that has learned about optimization methods and convergent geometric sequences, and the second can be presented after they have learned the Fundamental Theorem of Calculus. [ABSTRACT FROM AUTHOR]

Introduction: The ratio of Triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) is a crucial indicator for diabetes diagnosis. Methods: This study utilizes the Copula function to model and fit the non-linear correlation among fasting blood glucose (Glu), glycosylated hemoglobin (HbA1C), and TG/HDL-C in patients with diabetes. The Copula function chosen for this study includes the two-dimensional Archimedes and Elliptical distribution family, as well as the multidimensional Vine Copula function, for fitting the data. The evaluation of the fitting effect is performed using the mean absolute error (MAE) and mean square error (MSE). Results: The results indicate that the Clayton Copula exhibits the highest effectiveness in fitting the pairwise relationship between Glu and TG/HDL-C, as well as HbA1C and TG/HDL-C, displaying the smallest fitting error. Additionally, the Vine Copula function produces a satisfactory fit for the relationship among all three indicators. Compared to linear analysis methods, the Copula function more accurately depicts the correlation among these three types of indicators. Discussion: Moreover, our findings indicate a stronger correlation in the lower tail between Glu and HbA1C, as well as TG/HDL-C, suggesting that the Copula function provides greater accuracy and applicability in depicting the relationship among these indicators. As a result, it can offer a more precise auxiliary diagnosis and serve as a valuable reference in clinical judgment. [ABSTRACT FROM AUTHOR]

The surge of lightweight containers in cloud storage, propelled by technological advancements, offers dependable services. However, the inherent security concerns arising from shared access to the host Operating System (OS) necessitate an effective solution. This paper introduces an energy-efficient and secure scheduling approach to tackle this issue. Users register task requests with a resource manager, which collects and preprocesses data to eliminate redundancies. The Levenberg-Marquardt Multi-Layer Perceptron Neural Network (LM-MLPNN) optimizes container resource utilization by analyzing user requests. The Homography Transform-based K-Mode Algorithm (HT-KMA) facilitates efficient clustering through attribute extraction. To address imbalances, the Weighted Round Robin (WRR) technique is employed. An optimal container, selected by the Variational Mode Decomposition-based Archimedes Optimization Algorithm (VMD-AOA), undergoes Elliptic Curve-based Key Derivation Function (EC-KDF) for enhanced security before being transmitted to the resource manager. Experimental results demonstrate the superiority of our methodology over existing algorithms. [ABSTRACT FROM AUTHOR]

Titanium and its alloys are used to make dental implants because of its low density, high strength, and corrosion resistance. This paper describes the development of a potential biomaterial Ti‐10Nb by powder metallurgy utilizing four different compaction pressures and analyses its microstructural, physical, mechanical, electrochemical, biological, and tribological behavior under various situations. The alloys were fabricated using four different compaction pressures, that is, 600, 650, 700, and 750 MPa, and sintered in a vacuum atmosphere at 1000°C for 1.5 h. The density of the samples was measured using Archimedes principle. X‐ray diffraction and scanning electron microscopy equipped with energy dispersive spectroscopy were used to investigate the phase composition and microstructure, and a profilometer was used to examine the surface roughness of various samples. Vickers hardness tester was used to evaluate hardness, and a universal testing machine was used for compression testing. Corrosion and wear behavior were examined using a potentiostat and a Bio‐Tribometer, respectively. This Ti‐10Nb alloys consist of α + β phase, and have 16% highest porosity in sample compacted at 600 MPa. The samples compacted at 750 MPa achieved highest hardness, yield strength, compressive strength, and elastic modulus of 450 ± 29.72 HV, 718.22 ± 16.37 MPa, 1543.59 ± 24.37 MPa, and 41.27 ± 3.29 GPa, respectively. In addition, it also possesses highest corrosion and wear resistance with lowest icorr of 0.3954 ± 0.008 μA/cm2 and wear volume of (31.25 ± 0.206) × 10−3 mm3. These results indicate that the developed alloys have a variety of desirable properties, including high hardness, adequate compressive strength, good corrosion and wear resistance, apatite‐forming capability, and a low elastic modulus, which is advantageous for avoiding stress shielding. Therefore, it may be recommended to use it as a dental implant material. [ABSTRACT FROM AUTHOR]

Analyzing the landing dynamics response is essential for enhancing the success rate of surface explorations on celestial bodies like Mars, the moon, and asteroids. This paper develops a comprehensive dynamics model for a space lander equipped with four sets of buffer legs. Each set comprises a primary strut, two secondary struts, and a footpad. The compression force of the buffer struts is determined through interpolation of real experimental data, while the contact force between the footpad and the ground is calculated using Archimedes law for granular media. The Lagrange equation of the second kind is employed to construct the dynamical model for the lander with minimal degrees of freedom. The proposed dynamics model is validated through experiments involving touchdowns of a single legged lander and a four legged lander. Moreover, key physical quantities such as the buffer force, energy absorption and body acceleration are computed for both 1-2-1 and 2-2 landing configurations. The results indicate that the buffer strut is capable of absorbing approximately half of the impact energy, leading to a 50-fold reduction in the shock acceleration of the main body in both landing configurations. However, it is observed that the maximum compression of the buffer strut is greater in the 1-2-1 landing configuration than in the 2-2 landing configuration. Furthermore, these simulations can be completed within seconds, enabling extensive simulations for the design and optimization of soft landing processes. [ABSTRACT FROM AUTHOR]

Through an activation reaction sintering method, porous (Mo2/3Y1/3)2AlC ceramics were prepared by Mo, Y, Al, and graphite powders as raw materials. The phase composition, microstructure, element distribution, and pore structure characteristics were comprehensively studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), Archimedes method, and bubble point method. A detailed investigation was conducted on the influence of sintering temperature on the phase composition. Possible routes of phase transition and pore formation mechanisms during the sintering process were provided. The experimental results reveal that at 650–850 °C, transition metals react with aluminum, forming aluminum-containing intermetallics and a small amount of carbides. At 850–1250 °C, transition metals collaborate with graphite, producing transition metal carbides. Then, at 1250–1450 °C, these aluminum intermetallics interact with transition metal carbides and remaining unreacted Y, Al, and C, yielding the final product (Mo2/3Y1/3) 2AlC. Simultaneously, the pore structure alters correspondingly with the solid-phase reaction at different reaction temperatures. [ABSTRACT FROM AUTHOR]

Reducing the dependence on traditional energy sources and shifting towards the utilization of renewable energy sources (RES) of energy in the maritime sector is imperative for reducing greenhouse gas emissions. Inherently, RES sources like solar and wind are intermittent and variable, resulting in inconsistent power availability and hence leading to energy supply fluctuations and potential shortages. In this respect, an efficient control strategy to maintain system stability and address intermittency effectively is essential. This work considers a hybrid marine microgrid with various energy sources like photovoltaics (PV), wind energy conversion system (WECS), marine biodiesel generator, Archimedes wave power generation, solid oxide fuel cell, and batteries. A 2-degree of freedom (2DOF) structure is designed and implemented with the tilt-integral-derivative filter (TIDN) to address frequency variations. Furthermore, an Archimedes optimization algorithm (AOA) is used to optimize the 2DOF-TIDN controller. The stability of the proposed microgrid system is assessed under various combinations of RES availabilities, including real-time data from WECS and PV. The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. Simulation results obtained show that the AOA-based 2DOF-TIDN control strategy achieves shorter settling times in mitigating the changes of marine microgrid systems under different dynamic conditions as compared to the other algorithms. Finally, the controller being proposed in this paper was tested for robustness with parameter deviations of +25%, −20%, and − 40% from the nominal values, and proved to be the proposed 2DOF-TIDN controller parameters demonstrate significant robustness in effectively managing the uncertainties and parametric variations. • Maritime Microgrid system is designed for investigations with RE & storage units. • PV, Wind, MBG, AWPG, SOFC, and battery storage units are considered. • 2DOF-TIDN controller is developed to mitigate the changes in the system. • The AOA method is proposed for optimal gains of the 2DOF-TIDN under uncertainties. • Sensitivity analysis, Time delay analysis, and stability analysis are performed [ABSTRACT FROM AUTHOR]

This paper proposes an efficient method for calculating the dynamic behaviour and seismic performance of reciprocal structures by introducing the generalized displacements at the hinge point to describe the displacements of the nodes at the beam ends. The whole structural nodal coding system is condensed by replacing the two codes at the beam end nodes with code at the hinge point based on the traditional space rigid frame matrix displacement method. On the basis of the principle of virtual work, the system natural vibration equation of the structure in the condensed nodal coding system is obtained; from the mode-superposition response spectrum method and the time history analysis method, the system seismic response equation of the structure in the condensed nodal coding system is derived. Then, the dynamic behaviour and seismic performance of the structure can be achieved by solving the obtained system dynamic equations. Finally, two numerical examples, a space L-shaped articulated reciprocal rigid frame and a reciprocal configuration transformed from the 36 type of Archimedes paving, are adopted to demonstrate the effectiveness of the proposed method. From the numerical results, the reciprocal structure transformed from the 36 type of Archimedes paving has a large whole stiffness, and the seismic response generated by vertical earthquake excitation is the most significant, which should be the focus of the seismic design of reciprocal structures. The proposed method effectively reduces the number of computational degrees of freedom of the whole structure and is more efficient in calculating the reciprocal structure. • A new method for dynamic calculation of reciprocal structures is proposed. • The condensed nodal coding system is introduced. • The beam end nodal displacements are described by the generalized displacements at the hinge point. • The natural vibration equation and seismic response equation in the condensed nodal coding system is derived. • The dynamic behaviour and seismic performance of reciprocal structures are investigated. [ABSTRACT FROM AUTHOR]

• A novel MSSAO-ERNN technique is proposed to detect the PTSD symptom from speech. • The MSSAO-ERNN technique efficiently identifies PTSD symptoms from the dataset. • Three datasets namely NNE, FME hospital as well as TIMIT datasets are employed. • PTSD is mental illness that affects people when they experience traumatic events. • Performance is determined by computing various metrics for PTSD identification. Post-traumatic stress disorder (PTSD) is a stress-based disorder that occurs when a person is vulnerable to undesirable traumatic events like injury or harm. Numerous research works reported dissimilar complex issues for detecting PTSD severity in patients which makes the PTSD diagnosis process a complicated task. So, a novel Multi-Strategy Seeker Archimedes Optimization-based Elman Recurrent Neural Network (MSSAO-ERNN) technique to detect PTSD symptoms in earlier stages using speech samples. Our proposed MSSAO-ERNN technique efficiently identifies PTSD symptoms from the dataset and helps the physician to diagnose accurately. The proposed approach constitutes various significant phases that include the pre-processing phase, feature extraction phase, and classification phase to detect the presence of PTSD in the datasets. The performance of the proposed method is determined by computing various metrics for the accurate identification of PTSD. Finally, three different datasets namely the NNE dataset, the FME hospital dataset as well as TIMIT dataset are employed in this paper for PTSD diagnosis. The experimental results revealed that the proposed method attained a superior accuracy of 97% under different PTSD techniques. [ABSTRACT FROM AUTHOR]

With a growing interest on inorganic ceramics based solid-state electrolytes for all-solid-state batteries, there is a need to maximise their density to optimise electrochemical performance and fuel impermeability. In this paper, we demonstrate the sensitivity of terahertz time-domain spectroscopy (THz-TDS) combined with effective medium theory to quantify the porosity or density of sodium superionic conductor (NaSICON)-based solid-state electrolyte (SSEs) pellets prepared at densities in the range of 2.2–2.9 g cm−3, corresponding to 50–90 % relative densities sintered at 900–1150 °C. The results of which, have been validated against complementary Archimedes analysis and mercury porosimetry highlighting the potential of THz-TDS for rapid, contactless, non-destructive electrolyte characterisation. • Demonstrated sensitivity of terahertz radiation to NaSICON-based electrolyte. • NaSICON densities quantified using effective medium theory. • Estimated densities correlates to Archimedes analysis. • Estimated densities agrees with to mercury porosimetry data. [ABSTRACT FROM AUTHOR]

The impedance matching control, also known as approximate complex conjugate control (ACC), is one of the main strategies for improving the capture of energy by point absorber wave energy converters. Such a strategy shapes the mechanical impedance related to the floater dynamics via the control law. Since the traditional ACC is given by a linear control law, this work proposes a generalization denoted as nonlinear complex conjugate control (NCC) that considers the presence of nonlinear viscous damping in addition to the usual linear damping and stiffness. The energy maximization conditions for the proposed NCC are derived in the frequency domain through the describing function method. These conditions show that the ACC is a special case of the NCC when the total damping on the floater is approximated as a linear function of its velocity. From numerical simulations of a point absorber wave energy converters with nonlinear damping, which is based on the Archimedes wave swing prototype, it is shown that the NCC provides greater energy conversion than the ACC, as well as a robust performance in the presence of variations of the damping coefficient and the excitation force peak frequency. [ABSTRACT FROM AUTHOR]

The evolution of belt conveyors, as an important type of continuous conveying machinery, is examined here in a historical perspective. For this purpose, the selected period is from the ancient time, i.e. occurrence of conveying equipment, and up to the end of the nineteenth century. The basic postulation of a modern machine, including conveyors, is often interlinked to that of its ancestor, which may be simple and primitive. Ancient machines and principles of their work were the basis for later improvements which also brought the inventions in engineering. For instance, Archimedes lifted water to high altitude with a screw, which was regarded as the ancestor of today's screw conveyor and essentially his design has not changed since then. Bucket elevators also have their predecessors dating back to ancient times. In the concrete case of belt conveyors, a first trace can be found in the beginning of the seventeenth century, even classified as primitive example. During the Industrial Revolutions, various machines, such conveyors, appeared. The first modern-like belt conveyors are dedicated to the late eighteenth century due to the invention of Oliver Evans in USA and to the nineteenth century, by Lyster in England, Lopatine in Russia and Thomas Robins in USA. The technical solutions developed by the end of the nineteenth century were forerunners of the today's belt conveyors, while the key operational principles have not changed. [ABSTRACT FROM AUTHOR]

Archimedean spirals are common in various fields such as biology, engineering, astronomy, and space physics. Here we report the discovery of patterns resembling the general Archimedean spirals in particle distributions in the Earth radiation belt. Our analytic theory and numerical simulations demonstrate that electrons with initially asymmetric spatial distributions form such spirals in the inner magnetosphere, where particles at smaller radial distances move more slowly in angular velocity. These spirals result in time‐varying peaks and valleys in particle fluxes, referred to as "zebra stripes," which are well consistent with Van Allen Probes measurements. Although the initial asymmetric distribution may be seeded by the electric field in the magnetosphere, the spiral formation does not require them. Furthermore, we show that, due to the same fundamental motion of charged particles in regions dominated by dipole fields, this spiral phenomenon may also appear in the proton distributions, as well as in planetary magnetospheres. Plain Language Summary: The Archimedean spiral is named after the 3rd‐century BC Greek mathematician Archimedes. Such spirals have been seen from the sunflower head, Iridogorgia to galactic arms. Throughout the solar system, the average configuration of the background magnetic field also aligns with Archimedean spirals, as it is dragged by charged particles that are ejected radially from the surface of the rotating Sun, a fundamental discovery made by E. N. Parker. However, it remains unknown whether an Archimedean spiral exists in the near‐Earth space. Here we report for the first time the discovery of patterns similar to the general Archimedean spirals in particle distributions in the radiation belt, a region filled with energetic charged particles surrounding Earth. This happens because electrons closer to the Earth move slower in the angular direction. These spirals manifest as time‐varying peaks and valleys in the electron spectagrams, named as "zebra stripes." Our theory and simulation results are well consistent with the measurements of the Van Allen Probes. Besides, our theory predicts that these spirals could occur on protons and other planets with similar magnetic fields. Key Points: The first known discussion and discovery of Archimedean spiral structures in Earth's magnetosphereElectrons' general Archimedean spiral‐like distribution results in the formation of "zebra stripes" in the inner radiation beltOur findings hold exciting implications for understanding magnetospheric physics beyond our planet [ABSTRACT FROM AUTHOR]

A novel methodology for determining the singular point of an enveloped surface is put forward. Unlike some existing methods, the presented method starts directly from the equation of the enveloped surface instead of that of the generating surface, and it is thus called a direct method. The calculation for the normal vector of the enveloped surface is well simplified with the help of the moving frame approach, which makes the presented method feasible. The singularity condition equation is extracted by using the theory of linear algebra. For singular points with different properties, proper solving techniques are established, including resultant elimination and simple elimination. Applying the developed method, the undercutting characteristics of the Archimedes worm wheel are investigated from the perspective of spatial meshing. The numerical results demonstrate that the worm wheel generally has one undercutting limit line, whose trend is along the tooth width of the wheel. Locating on one side of the tooth surface and near the tooth root is a dangerous part of the worm wheel undercutting. The proposed method is beneficial for the development of gear meshing science. [ABSTRACT FROM AUTHOR]

A symbolic analysis of Archimedes's periodical number system is developed, from which a natural link emerges with the modern positional number systems with zero. After the publication of Fibonacci's Liber Abaci, the decimal Indo-Arabic positional system was the basis of the algorithmic and algebraic trend of modern mathematics, but even if zero plays a crucial role in algebra and mathematical analysis, zeroless positional systems show the same capability of producing efficient arithmetical algorithms based on operation tables over digits. The crucial role of digits is assessed, by considering a representation of numbers based on strings in lexicographic order. A new algorithm for the determination of decimal periods is presented by remarking on the cruciality of this topic in number theory. Periods of ordinal numbers and enumerations of recursive enumerability are shortly recalled. Concluding remarks are formulated about the deep relationship between numbers and information, which shed new light on a red line passing through the whole history of mathematics. [ABSTRACT FROM AUTHOR]

In this study, a nonlinear Archimedes wave swing (AWS) energy conversion system was employed to enable the use of irregular sea waves to provide useful electricity. Instead of the conventional PI controllers used in prior research, this study employed fractional-order PID (FOPID) controllers to control the back-to-back configuration of AWS. The aim was to maximize the energy yield from waves and maintain the grid voltage and the capacitor DC link voltage at predetermined values. In this study, six FOPID controllers were used to accomplish the control goals, leading to an array of thirty parameters required to be fine-tuned. In this regard, a hybrid jellyfish search optimizer and particle swarm optimization (HJSPSO) algorithm was adopted to select the optimal control gains. Verification of the performance of the proposed FOPID control system was achieved by comparing the system results to two conventional PID controllers and one FOPID controller. The conventional PID controllers were tuned using a recently presented metaheuristic algorithm called the Coot optimization algorithm (COOT) and the classical particle swarm optimization algorithm (PSO). Moreover, the FOPID was also tuned using the well-known genetic algorithm (GA). The system investigated in this study was subjected to various unsymmetrical and symmetrical fault disturbances. When compared with the standard COOT-PID, PSO-PID, and GA-FOPID controllers, the HJSPSO-FOPID results show a significant improvement in terms of performance and preserving control goals during system instability [ABSTRACT FROM AUTHOR]

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