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In order to examine the 5G enhancement, this work generates a variety of Filtered-Orthogonal Frequency Division Multiplexing (F-OFDM) waveforms. Windowed-Sinc filters are studied to deploy waveforms in real time. The Blackman-Harris window and the Bohman window have been combined to create a new window, which has been studied. Waveforms built utilizing this window have been compared to traditional Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) waveforms using the MATLAB evaluation package. Data from simulations reveals a number of tradeoffs between bit error rate (BER) and power spectral density. The designer, however, has some leeway in how the window is used. However, BER and power spectral density (PSD) measurements demonstrate that the windows chosen for this work nearly outperform the CP-OFDM signal. Compared to the central lobe, the sidelobe PSD of CP-OFDM is found to be close to -50dBW/Hz. However, -214.177 dBW/Hz is the value obtained for the new-window. [ABSTRACT FROM AUTHOR]

Abstract This study introduces three soft computing (SC) optimization algorithms aimed at enhancing the efficiency of photovoltaic water pumping systems (PVWPS). These algorithms include the Gorilla Troop Algorithm (GTO), Honey Badger Algorithm (HBA), and Snake Algorithm (SAO). The goal of the SC optimizers is to maximize the output power of the PV array (P PV ) and enhance the efficiency of the DC motor (η), thereby optimizing the water flow rate (Q) of the pumping system. The analytical modeling approach proposed in this study involves forecasting the optimal duty cycle (D op ) for a buck-boost converter, taking into account variables such as solar radiation (G) and ambient temperature (T). A comparative analysis is conducted between the suggested SC optimizers and analytical modeling. MATLAB simulation is employed to explore an adaptive neuro-fuzzy inference system (ANFIS) trained for the proposed system. The objective is to assess system performance and accuracy. Findings indicate a strong convergence between the analytical model and the simulation model utilizing SC optimizers. Moreover, the neuro-fuzzy system trained offline, coupled with the proposed SC optimizers, demonstrates superior performance compared to traditional control methods like perturb and observe (P&O) and incremental conductance (IC). This superiority is evident across various metrics including motor efficiency (η), photovoltaic (PV) output power (P PV ), water flow rate (Q), and time response.

[Objective] To meet the requirements of constant and adjustable rotation speed of rolling barrel and constant rotation speed of rolling barrel when tea is rolled. [Methods] The 6CR-55 single-column disc twisting machine was used as the research object in this paper. Fuzzy control algorithm and PWM closed-loop control method were investigated to study the stable control of rotating speed of rolling drum, and established the mathematical model of rotating speed control system of rolling drum based on the STM32 single-chip microcontroller. The simulation experiments of uncorrected, PID and fuzzy PID algorithm control system were carried out by MATLAB. [Results] Compared with uncorrected control and PID control, the output speed of the fuzzy PID speed control system was more stable and accurate, and the anti-interference ability was stronger. The speed error was controlled within 3 r/min. [Conclusion] The fuzzy PID control method can meet the requirement for the constant and adjustable rotating speed of the rolling drum during tea rolling, and improve the rate of tea forming and cell breakage.

Featured Application: A novel active range while drilling method, based on the drilling well, with dual-electrode current excitation, is proposed. The range while drilling model utilizing dual-electrode current excitation is established, and the calculation methods for the current amplitude of the casing and the formation-induced magnetic field distribution are derived. The accuracy and effectiveness of this approach are validated through numerical calculations and simulation analyses of the impact of each key factor. It is particularly appropriate for targeted well ranging operations that entail safety risks, especially in the relief well connectivity operations at space-constrained drilling platforms. Based on a comprehensive analysis of the existing methods for measuring adjacent well distances, along with their advantages and disadvantages, this study employs theoretical analysis, simulation experiments, and other comprehensive research methods to investigate a distance measurement method based on current excitation. In response to the need for measuring and controlling the connection of relief wells, a method utilizing dual-electrode current excitation during drilling is proposed. This approach facilitates synchronous excitation measurements while drilling, significantly reducing both time and costs while ensuring safety and efficiency, making it particularly suitable for the connection operation of relief wells that involve safety risks. Firstly, this paper establishes a drilling with measurement model corresponding to the excitation mode, which derives the calculation formulas for the target casing current amplitude attenuation, as well as the induced magnetic field distribution within the formation. Additionally, it provides the calculation methods for determining the target well distance and azimuth direction. Lastly, the impact levels of various key factors are verified through numerical calculations and simulation analyses, which confirm the correctness and effectiveness of this distance measurement method. The findings from this research establish both a core theoretical foundation and a technological basis for the real-time measurement of adjacent well distances during relief well operations. [ABSTRACT FROM AUTHOR]

ABSTRACT This study delves into the advancements, challenges, and opportunities in the solar grid technology, emphasizing its integration into the existing power infrastructure. The proposed ML‐FOGI (multilayer fourth‐order generalized integrator) algorithm presents a promising solution for modern grid synchronization requirements, addressing challenges posed by the integration of renewable energy into the distributed generation. This technology enhances system robustness and dynamic response, particularly in weak distribution grids characterized by voltage distortions and imbalances. This innovative approach enhances system stability and performance, particularly in polluted grid conditions. Through MATLAB/Simulink modelling and experimental validation, the effectiveness of the proposed control strategy is investigated across diverse testing conditions. Emphasizing the significant role of the control strategy in enhancing power quality and grid stability in the solar photovoltaic systems, this research underscores the importance of robust and adaptive control mechanisms for optimizing performance and ensuring grid reliability in modern microgrid. This study delves into this complex issue of working of the grid connected photovoltaic (GCPV) system, emphasizing the importance of balanced unit templates and a stable DC link voltage with unpredictable grid harmonics. This research aims to enhance the resilience of solar PV systems against grid disturbances by drawing inspiration from the adaptable nature of ADALINE filters and adhering to the IEEE519 requirements. This study employs OPAL‐RT's resilient experimental configuration. [ABSTRACT FROM AUTHOR]

This study proposes intelligent control strategies for optimizing the grid integration of photovoltaic (PV) and wind energy in hybrid systems using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS control aims to enhance grid stability, improve power management, and maximize renewable energy (RE) utilization. The hybrid system's performance is evaluated through simulations, considering various environmental conditions and load demands. Results demonstrate the effectiveness of the proposed ANFIS-based control in dynamically adjusting the power output from PV and wind sources, ensuring efficient grid-connected operation. The findings underscore the potential of intelligent control strategies to contribute to the reliable and sustainable integration of RE into the grid. [ABSTRACT FROM AUTHOR]

Phase unwrapping technology can reflect the true phase information of an image, but it is affected by adverse factors such as noise, shadows, and fractures when extracting the true phase information of an object. Therefore, corresponding unwrapping algorithms need to be studied for different interference images. This paper summarizes and analyzes various phase unwrapping algorithms and ultimately selects the required method based on their advantages and disadvantages. Using the four-step phase-shift method to reconstruct the phase of the optical field and then combining it with the least squares method to unwrap the phase through multiple improvement iterations, the simulated collected interference fringe images are simulated using the MATLAB program to complete the phase unwrapping of the interference information field. Based on the analysis of the final experimental results, the reliability of this research method was verified. [ABSTRACT FROM AUTHOR]

In order to solve the problems of long adjustment time and poor stability of the commonly used speed current variable frequency negative feedback speed control system in engineering, the author proposes an improved fish school algorithm application method in variable frequency speed control systems. A fish swarm algorithm optimized based on the arena method is applied to a variable frequency speed control system, and the optimization algorithm is applied to the speed control system to screen the PI parameters that meet the requirements of the speed control system. The simulation results show that compared with manual parameter tuning, the controller parameters optimized by the improved fish school algorithm have better control performance. In the absence of overshoot starting, the starting time was shortened by 0.21s, and the system response speed was improved. When a sudden load of 6 N m is applied, the speed drop is reduced by 3 r · min−1, and the recovery time is shortened by 0.15 s, resulting in stronger anti-interference performance of the system. Conclusion: The new algorithm shortens the control time and improves the robustness of the system.

These days, one of the most used layouts in the wind power industry is a variable-speed doubly-fed induction wind generator (DFIWG). For providing active power (P) and reactive power (Q) control during grid failures, this research examines the DFIWG. The system's transient behavior is examined under normal and abnormal circumstances. Through control of rotor side (RSC) and grid side (GSC) converters, Q assistance for the grid, and power converter stress reduction, the suggested control approach achieves system stability while enabling DFIWG to operate smoothly during grid failures. The DFIWG is exposed to three- and two-phase faults to analyze the machine's performance. The crowbar and STATCOM tools are implemented to enhance the system performance under faults and compared with the base case. The implemented tools successfully suppress rotor and stator overcurrent, over voltage at the DC link (DCL), and power oscillations, as well as supporting the grid voltage understudied cases. The obtained results prove that both STATCOM and crowbar not only enhance the system's effectiveness and performance but also enable the system to achieve the fault ride-through capacity (FRTC). MATLAB/SIMULINK 2017b is used for time-domain computer simulations. [ABSTRACT FROM AUTHOR]

One of the most important and desirable options for moving toward clean electric energy sources is solar energy. Therefore, a PV system's characteristics play a significant role in determining how effective it is across a range of temperature and radiation scenarios. One can consider the PV model's parameter estimation to be a nonlinear optimization situation. This work makes use of a novel application of the smell agent optimizer (SAO) created to forecast the undefined parameters of the PV model's single- and two-diode equivalent circuits. The goal of this effort is to create an accurate photovoltaic model that can accurately represent its performance under variable operating conditions. The square of the mean squared error between the actual measured curve and the current-voltage curve derived from the model defines the intended objective function. The suggested system is constructed and tested experimentally in a range of temperature and light conditions. Next, the MATLAB software is used to create the simulated PV model integrated with the SAO. The PV parameters are then predicted by comparing the experimental data with the convergence of the SAO based on the PV model. Based on the observed properties, the suggested approach for determining the parameters of an actual solar cell has been put into practice and contrasted with eight other optimization techniques. The outstanding efficacy of the method utilized compared with alternate methods is demonstrated by the statistical comparison of the ideal objective function resulting from the difference in the current-voltage curve produced from the optimized circuit model and the measurement. [ABSTRACT FROM AUTHOR]

The practices of prefabricated buildings illustrate the incentives in prefabricated markets as well as the decision-making behavior of stakeholders, which can influence the transformation, upgrading, and sustainability of the buildings sector. The game between the stakeholders in the prefabricated buildings market becomes complicated by the fact that they dynamically adjust their strategies in response to changing market conditions. With the aim of quantitatively studying the implications of the dynamic decision behavior of prefabricated construction stakeholders on the prefabricated construction market, this study introduces component suppliers as participating agents and government subsidies and penalties as the main measures. And a three-way model of the evolutionary game involving government subsidies and punitive schemes is constructed by this study. The essay examines the evolutionary equilibrium strategies of each game subject as well as the effect of original strategies and different parameter choices on the decision-making of each subject using MATLAB. The findings reveal that (1) decision-making behaviors among the government, component suppliers, and developers are both interrelated and constrained, but governments are the dominant agents in the evolution of prefabricated buildings. (2) Parameters such as subsidies, penalties, costs, and benefits affect the stability of the tripartite evolutionary model, which remains consistent with the previous research. (3) Component suppliers have an equally important position in the development of prefabricated buildings as recognized entities such as developers and contractors. (4) When subsidies are kept at 40% of the incremental cost and penalties at 80% of the incremental cost, the model combines a fast evolutionary rate with stable model evolution. In conclusion, the article's research findings not only validate the rationality and feasibility of component suppliers as research subjects and confirm the importance of component suppliers but also propose a more reasonable boundary value for penalties and subsidies, which provides a reference for the government to improve the incentive and punishment measures as well as the dynamic adjustment strategy of stakeholders and also provides a new perspective to achieve the goal of sustainable development of construction. [ABSTRACT FROM AUTHOR]

The efficient placement of Phasor Measurement Units (PMUs) is crucial to minimize their number while ensuring full power system observability. A power system is deemed observable when the voltage at every bus is known. This study proposes a topology transformation approach that combines a Zero-Injection Bus (ZIB) with one of its neighboring buses to achieve optimal PMU placement. The choice of the neighboring bus for combination with the ZIB significantly influences the outcome of the merging process. To identify the optimal candidate bus for merging with the ZIB, the proposed approach utilizes three selection principles aimed at determining the minimal number of PMUs necessary for complete system observability. This study also examines the scenario of power flow measurements, formulating the problem using Integer Linear Programming (ILP). The effectiveness of the proposed method is demonstrated through simulations conducted in MATLAB on various IEEE Bus systems, with a detailed explanation provided using the IEEE 14-Bus system. Comparative analysis reveals that the number of PMUs obtained with the suggested method is competitive with existing techniques. Furthermore, this study includes a comparison between the IEEE 30-Bus and IEEE 14-Bus systems by inducing faults at specific buses. This is done to verify whether PMUs placed at optimal locations ensure complete coverage of all buses in both systems. The comparison also extends to evaluating the cost implications of placing PMUs solely at these optimal locations. [ABSTRACT FROM AUTHOR]

As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan. This research presents an innovative simulation of a 4S3P lithium-ion battery pack using MATLAB R2023b, designed to refine BMS capabilities by employing advanced mathematical modelling and computational intelligence. The simulation meticulously analyses critical operational metrics such as state of charge (SOC), state of health (SOH), temperature variations, and electrical behaviour under diverse load scenarios, offering deep insights into the intricate dynamics of lithium-ion batteries in EV applications. The results corroborate the simulation model's accuracy in reflecting actual battery pack performance and underscore significant improvements in BMS strategies, especially concerning predictive maintenance and adaptive charging techniques. By seamlessly integrating computational intelligence into BMS, this study lays the groundwork for more durable, efficient, and intelligent energy storage systems in electric vehicles, marking a significant stride in e-mobility technology. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) technology is a contactless wireless energy transfer method with wide-ranging applications in fields such as smart homes, the Internet of Things (IoT), and electric vehicles. Achieving optimal efficiency in wireless power transfer systems has been a key research focus. In this paper, we propose a tracking method based on full current mode impedance matching for optimizing wireless power transfer efficiency. This method enables efficiency tracking in WPT systems and seamless switching between continuous conduction mode and discontinuous mode, expanding the detection capabilities of the wireless power transfer system. MATLAB was used to simulate the proposed method and validate its feasibility and effectiveness. Based on the simulation results, the proposed method ensures optimal efficiency tracking in wireless power transfer systems while extending detection capabilities, offering practical value and potential for widespread applications. [ABSTRACT FROM AUTHOR]

Fan power generation, a form of new energy, has gained significant attention. However, as fan capacities grow, the challenges in the development process also increase. A wind maneuver model experiment system must be constructed to simulate the actual fan operation dynamics. The wind turbine simulator is essential for conducting experiments on wind turbines and advancing the research of wind power production technology. However, due to the insufficient moment of inertia in wind turbine simulators under laboratory conditions, physical compensation methods are challenging to implement. Therefore, most scholars rely on software compensation algorithms to realize the stability simulation of wind turbine simulators with small moments of inertia and actual wind turbines with large moments of inertia. Under this research background, this paper presents the existing moment of inertia compensation strategies based on current research hotspots. The theoretical foundation covers the mechanical dynamic models of both actual wind turbines and simulators along with an analysis of inertia compensation strategies, including high-order filters and feedforward bias suppression. Finally, the Simulink simulation platform is used to compare and validate the effectiveness of these strategies.

In this study, a MATLAB simulation model was developed for the purpose of calculating the energy dissipation of runoff over submersible dams. A laboratory model of a submersible dam with standard dimensions was used, and two angles of inclination of the dam surface 16° and 24.5° were used downstream. In the laboratory work, the discharge and water depth were measured, in addition to the length of the hydraulic jump and the distance from the source, and by using the basic flow equations, the percentage of flow energy dissipation was calculated for both models, and the discharges were counted. The values of the Froude number ranged from 3.612 to 10.784. A simulation model was built in the MATLAB program using the basic equations of flow, finding the values of energy dissipation percentage and comparing them with the laboratory results. Then drawing the relationships between each of the discharge (Q), energy dissipation percentage (E%), Froude number (Fr), hydraulic jump length (Lj), and the distance of the hydraulic jump from the submerged dam (Dj). The numerical and experimental data have been compared, and it has been determined that there is an acceptable agreement between them. The results also showed the efficiency of using the MATLAB simulation method to obtain accurate and fast results. [ABSTRACT FROM AUTHOR]

In order to achieve accurate transmission of protection signals in fiber optic communication networks, it is necessary to perform channel balancing configuration of fiber optic communication networks and adaptive forwarding control processing of relay protection signals, the author proposes an accurate transmission method for relay protection signals in fiber optic communication networks based on time-varying multipath fading suppression and adaptive beamforming. The system analyzes the sources of wireless long-distance pain signal interference signals, introduces anti-interference technologies such as two-dimensional joint processing (STAP), provides anti-interference algorithms and related gain analysis, and conducts signal processing gain simulation using MATLAB. Based on the analysis of comprehensive simulation results, at a given symbol length, the signal bandwidth increases, and the processing gain infinitely approaches the given theoretical limit value, rather than increasing nonlinearly. The reason is that the channel is affected by noise, and the channel estimation value and signal conjugate multiplication produce a noise quadratic term. At this point, the estimated value of the coherent region channel is reduced by the influence of noise, and the signal-to-noise ratio loss caused by the noise quadratic term is reduced, so the processing gain increases. During the process of infinite increase in signal bandwidth, the input signal-to-noise power ratio of the receiver tends to decrease towards an infinite value, limited by the size of the coherent region. The channel estimation value increases under the influence of noise, and the noise quadratic term is the main factor affecting the output noise power. When the symbol length is greater than the coherent time, the smaller the maximum Doppler frequency shift and the larger the coherent detection area, the greater the processing gain. [ABSTRACT FROM AUTHOR]

This study presents the development and examination of a streamlined $H_{\infty }$ loop-shaping continuous-time controller tailored for nonlinear Hard Disk Drive (HDD) systems. Using the Hankel-norm approximation technique, the complexity of the controller is systematically reduced, emphasizing preserving the system’s efficacy while enhancing computational efficiency. The dynamics of the HDD system and the performance of the proposed controller are investigated through MATLAB simulations. The effectiveness of the controller is quantitatively measured by employing the ITAE (Integral of Time multiplied by Absolute Error) criterion. The results indicate that a controller of the 10th-order provides a desirable compromise between maintaining robust control and minimizing disturbances and noise without significant loss in performance. This method illustrates the capacity for implementing more straightforward controllers in complex HDD systems, paving the way for their application in precision-critical industrial settings.

Based on a comprehensive analysis of the existing methods for measuring adjacent well distances, along with their advantages and disadvantages, this study employs theoretical analysis, simulation experiments, and other comprehensive research methods to investigate a distance measurement method based on current excitation. In response to the need for measuring and controlling the connection of relief wells, a method utilizing dual-electrode current excitation during drilling is proposed. This approach facilitates synchronous excitation measurements while drilling, significantly reducing both time and costs while ensuring safety and efficiency, making it particularly suitable for the connection operation of relief wells that involve safety risks. Firstly, this paper establishes a drilling with measurement model corresponding to the excitation mode, which derives the calculation formulas for the target casing current amplitude attenuation, as well as the induced magnetic field distribution within the formation. Additionally, it provides the calculation methods for determining the target well distance and azimuth direction. Lastly, the impact levels of various key factors are verified through numerical calculations and simulation analyses, which confirm the correctness and effectiveness of this distance measurement method. The findings from this research establish both a core theoretical foundation and a technological basis for the real-time measurement of adjacent well distances during relief well operations.

For the voltage stability enhancement of power system, the reactive power compensation is vital important. With the advancement in technology, the Flexible AC Transmission System Devices (FACTS) are widely used for stability improvement. In the primary substation, the stability is poor due to load conditions and system faults. In this research, the voltage stability enhancement for a Primary Substation using Static VAR (volt-amp reactive) compensator (SVC) is presented. SVC can be used to improve system voltage stability and addition of damping control. With the application of SVC, the voltage stability can be improved under normal condition as well as under contingency conditions. Shunt reactive power sources, including capacitive and inductive, are controlled by high power electronic switching devices in an SVC to enhance voltage stability. The goal of this attempt is to use SVC to improve the voltage stability of the 230/33 kV system. To evaluate the voltage stability improvement by SVC, a simulation model is implemented in Matlab/Simulink and performance analysis are carried out based on the simulation results.

Growing demand for renewable and sustainable energy sources has prompted research into bioethanol production as a viable alternative to hydrocarbon fuel for automobile engines. Based on their high carbohydrate content, Chlorella vulgaris microalgae were chosen for this study as a feasible biomass for bioethanol synthesis. After conducting microwave-based acid hydrolysis with varying acid concentrations of sulfuric acid (H2SO4) for 1–15 min, this study found that 3% H2SO4 for 5 min yielded the highest yield of reducing sugar (6.77 g/L). In this work, the RSM approach of central composite design (CCD) was utilized for modeling and optimization of ethanol fermentation and the MATLAB Simulink approach was employed for the simulation of ethanol fermentation. This study compared the effects of using Saccharomyces cerevisiae yeast for fermentation at different fermentation times (12 to 48 h), temperatures (28 to 32°C), and size of inoculum (0.5–1.5 g/L). Based on the actual and predicted results, the best conditions for fermentation were 36 h of time, 30°C of temperature, and 1.5 g/L of inoculum size. This gave the maximum ethanol concentration of 3.31 g/L. Furthermore, the RSM method provides minimum error and maximum R² value results for ethanol production compared to MATLAB simulation prediction (MSP). In addition, residue biomass from biofuel production is evaluated for its suitability for a further form of biofuel production. This research explores the opportunities for zero-waste biomass utilization in the development of biofuels. [ABSTRACT FROM AUTHOR]

This paper explores the potential of bifacial solar panels in desert environments, focusing on their integration with Artificial Intelligence (AI) for optimal energy generation. Bifacial panels, capturing sunlight from both sides, are well-suited for high-albedo desert regions but face challenges such as dust accumulation, high temperatures, and wind resistance. This paper will examine the role of AI-driven optimization systems in improving solar panel efficiency and their integration with Smart Cyber-Physical Systems (CPS) in agriculture and industry. To address existing research gaps, the proposed solutions include AI-based cleaning mechanisms, advanced cooling systems, and enhanced machine learning algorithms tailored for extreme environmental conditions. [ABSTRACT FROM AUTHOR]

Due to its long-range detection capabilities and resilience in a variety of weather conditions, radar technology is essential for Autonomous Vehicles (AVs) which are managed by Advanced Driver-Assistance Systems (ADAS). This review addresses critical aspects to enhance object detection in autonomous vehicles, focusing on the integration of radar systems with other sensor technologies such as LiDAR and cameras. By examining recent advancements in radar signal processing and machine learning algorithms, this review highlights the improvements in detection accuracy and reliability. Additionally, it discusses the challenges of radar interference and proposes potential solutions to mitigate these issues. [ABSTRACT FROM AUTHOR]

The location of Low-Altitude Flight Service Station (LAFSS) is a comprehensive decision work, and it is also a multi-objective optimization problem (MOOP) with constraints. As a swarm intelligence search algorithm for solving constrained MOOP, the Immune Algorithm (IA) retains the excellent characteristics of genetic algorithm. Using some characteristic information or knowledge of the problem selectively and purposefully, the degradation phenomenon in the optimization process can be suppressed and the global optimum can be achieved. However, due to the large range involved in the low-altitude transition flight, the geographical characteristics, economic level and service requirements among the candidate stations in the corridor are quite different, and the operational safety and service efficiency are interrelated and conflict with each other. And all objectives cannot be optimal. Therefore, this article proposes a Modified Immune Algorithm (MIA) with two-layer response to solve the constrained multi-objective location mathematical model of LAFSS. The first layer uses the demand track as the cell membrane positioning pattern recognition service response distance to trigger the innate immunity to achieve the basic requirements of security service coverage. In the second layer, the expansion and upgrading of adjacent candidate sites are compared to the pathogen's effector, and the adaptive immunity is directly or indirectly triggered again through the cloning, mutation and reproduction between candidate sites to realize the multiobjective equilibrium of the scheme. Taking 486,000 km2 of Sichuan Province as an example, MIA for LAFSS is simulated by the MATLAB platform. Based on the Spring open source application framework of Java platform, the cesiumjs map data is called through easyui, and the visualization of site selection scheme is presented with the terrain data of Map World as the background. The experimental results show that, compared with dynamic programming and ordinary immunization, the immune trigger mode of double response and the improved algorithm of operation parameter combination designed by the Taguchi experiment, the total economic cost of location selection is reduced by 26.4%, the service response time is reduced by 25%, the repeat coverage rate is reduced by 29.5% and the effective service area is increased by 17.5%. The security risk, service efficiency and location cost are balanced. The present work is to provide an effective location method for the layout number and location of local transfer flight service stations. For complex scenes with larger scale of low-altitude flight supply and demand and larger terrain changes in the region, the above research methods can be used to effectively split and reduce the dimension. [ABSTRACT FROM AUTHOR]

Phase unwrapping technology can reflect the true phase information of an image, but it is affected by adverse factors such as noise, shadows, and fractures when extracting the true phase information of an object. Therefore, corresponding unwrapping algorithms need to be studied for different interference images. This paper summarizes and analyzes various phase unwrapping algorithms and ultimately selects the required method based on their advantages and disadvantages. Using the four-step phase-shift method to reconstruct the phase of the optical field and then combining it with the least squares method to unwrap the phase through multiple improvement iterations, the simulated collected interference fringe images are simulated using the MATLAB program to complete the phase unwrapping of the interference information field. Based on the analysis of the final experimental results, the reliability of this research method was verified.

As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan. This research presents an innovative simulation of a 4S3P lithium-ion battery pack using MATLAB R2023b, designed to refine BMS capabilities by employing advanced mathematical modelling and computational intelligence. The simulation meticulously analyses critical operational metrics such as state of charge (SOC), state of health (SOH), temperature variations, and electrical behaviour under diverse load scenarios, offering deep insights into the intricate dynamics of lithium-ion batteries in EV applications. The results corroborate the simulation model’s accuracy in reflecting actual battery pack performance and underscore significant improvements in BMS strategies, especially concerning predictive maintenance and adaptive charging techniques. By seamlessly integrating computational intelligence into BMS, this study lays the groundwork for more durable, efficient, and intelligent energy storage systems in electric vehicles, marking a significant stride in e-mobility technology.

The use of industrial robots based on MATLAB simulation for water environment monitoring is to monitor the water environment better, improve monitoring efficiency and reduce monitoring costs. The robot can better collect data and can engage in deeper water-specific information. In this paper, based on the discussion of the water environment monitoring robots used in countries around the world for water environment monitoring, we introduce a MATLAB-based simulation of industrial robots in a wide range of water environments to simulate the autonomous data acquisition system. The main advantages are: compared with other robots, it can realize the “wide range” of water environment data collection; compared with fixed buoys, it can realize the “autonomous” collection of water environment monitoring data and gives the autonomous collection process and hierarchical software progression. The autonomous acquisition process and hierarchical software architecture are presented. The simulation results analysis shows no difference between the simulated data and the predicted data from the historical data using MATLAB-based industrial robots for water environment monitoring. This shows that the development of industrial robot simulation in water environment monitoring is promising and feasible.

The International Water Association's (IWA) established Anaerobic Digestion Model No. 1 (ADM1) was created to serve as a backup for experimental findings regarding the actual anaerobic digestion process. The previous model idea was adjusted and used to simulate an anaerobic digestion process in this study. Testing procedures, such as benchmark tests and balance checks, were performed in order to verify the accuracy of the implementation. These measures worked in tandem to ensure that the model was implemented flawlessly and without inconsistencies. The primary objective of this article is to construct a method that is based on the ADM1 for evaluating co-digestion and predicting the performance of the digestion process or methane yield based on the analyzed substrates' physicochemical properties. Additional equations and simulations have been added to the standard model to create tools for evaluating the feasibility of anaerobic co-digestion. The study's two most intriguing aspects are the optimal mixture and parameter dependence. The adjusted ADM1 is accurate in predicting the measured values of effluent COD, pH, methane, and produced biogas flows with a reasonable degree of accuracy, according to the validation results. This research shows how to use ADM1 in a wastewater treatment plant and other settings where anaerobic digestion is of interest. [ABSTRACT FROM AUTHOR]

This study investigates the substantial contribution of the recent numerical optimization technique known as the White Shark Optimizer (WSO) to evaluate the performance of proton exchange membrane fuel cell (PEMFC) design parameters that play a considerable role in boosting its effectiveness. A numerical code was developed and implemented via MATLAB software to achieve the research goal. The proposed WSO was employed to identify the unknown parameters of the PEMFC equivalent circuit, considering experimental data. The analyzed objective function was the root mean squared error (RMSE) between the measured and estimated fuel cell terminal voltages. Additionally, the proposed WSO was compared with other intelligent approaches such as the salp swarm algorithm (SSA), Harris hawks optimization (HHO), atom search optimization (ASO), dung beetle optimization algorithm (DBOA), stochastic paint optimizer (SPO), and comprehensive learning Archimedes optimization algorithm (HCLAOA). The numerical simulations revealed that the RMSE values varied between lower and higher values of 0.009095329 and 0.028663611, respectively. Additionally, the results indicated that the mean fitness value recorded in the considered PEMFC 250 W stack was 0.020057775. Moreover, the minimum fitness value was obtained using the proposed WSO, with an operating temperature of 353.15 K and working anode and cathode pressures are 3 bar and 5 bar, respectively. The proposed WSO offered the best results in terms of absolute errors compared to the other optimizers, confirming the robustness of the results in all considered cases. [ABSTRACT FROM AUTHOR]

The paper considers transients in an autonomous power system consisting of a generator, a transformer, and a general load. The numerical method for simulating transients includes the possibility of the asymmetry of stator windings and magnetic core saturation of a generator and a transformer. The asymmetry is usually observed under synchronous machine faults such as turn-to-turn short circuits in the stator winding. The method is based on the solution of differential equations for the equilibrium of electromotive force and voltage drops in windings in phase coordinates in combination with the rotor rotation equation. In this case, a circuit of each phase stator winding is described by an equation that considers the difference in phase parameters. The mathematical model is developed in MATLAB. The model includes an unequal number of turns in phase windings that allows simulating the turn-to-turn short circuits without considering the occurrence of additional short-circuited circuits. The analysis of simulation results was performed under no-load operating conditions and in the presence of load. The obtained results demonstrated the influence of the saturation of magnetic systems on the parameters of normal and abnormal operating conditions in the power system.

The management of municipal solid waste presents significant challenges globally. This study investigates the potential of an integrated waste-to-energy system based on circulating fluidized bed gasification technology to address these challenges, while also contributing to renewable energy generation. Using a MATLAB-based simulation model, the study determines the optimal operational parameters for various units within the system, including waste processing, gasification, ash handling, syngas treatment, and emission control. The proposed waste-to-energy system demonstrates a remarkable energy efficiency of 70% under these optimal conditions, notably outperforming conventional waste-to-energy technologies. Sensitivity and uncertainty analyses reveal that waste composition, gasification temperature, and the oxygen-to-solid recovered fuel ratio are key determinants of the system's output and performance. The system's performance remained robust despite variations in these parameters, underscoring its potential as a reliable solution for waste management and energy generation. While the findings are promising, future research should focus on comprehensive lifecycle assessment and consider regional factors for practical implementation. This study contributes to the ongoing development of efficient waste-to-energy systems and highlights their potential in promising sustainable waste management and renewable energy production. [ABSTRACT FROM AUTHOR]

The stability of railway locomotive is closely related to the safety of railway transportation. A new method for assessing the stability of railway locomotives uses Virtual Reality (VR) technology in conjunction with a dynamic simulation exercise. This paper develops the virtual test technology of railway locomotive running stability and its prototype system, thus shortening the development cycle and guaranteeing the running safety. Additionally, this paper uses numerical simulation and VR as technical support to make a more accurate evaluation of locomotive running stability. This paper utilizes the robust scientific calculation and numerical simulation functions of Matlab and Simulink to realize the simulation control of vehicle model motion and realizes the visual interactive display of railway locomotive running stability test results to realize the automatic analysis and calculation of various railway locomotive coefficients. In the meantime, this paper develops and implements a virtual overhaul system of a railway locomotive based on VR technology and simulates the process of equipment overhaul and disassembly on CAD software in order to ensure the daily inspection, maintenance, and repair of mechanical and electrical equipment of EMU. The system's test results demonstrate that: (1) Matlab can be used as the calculation kernel to realize anti-derailment, anti-overturning, numerical simulation analysis, and calculation of hunting stability of railway locomotives, providing more precise data support for the stable operation of locomotives. (2) The VR-based mechanical and electrical equipment maintenance system can satisfy the needs of maintenance personnel's visual inspection and disassembly simulation in the virtual maintenance environment and improve the realism of the simulation. In order to provide a more accurate virtual simulation of running stability and equipment identification of railway locomotives, the real-time presentation of vehicle stability characteristics in dynamic operation is investigated in this paper. [ABSTRACT FROM AUTHOR]

Some coastal cities are sometimes exposed to floods, mainly caused by strong winds or earthquakes on the seafloor. This causes the water waves heading to the coastal cities to rise quickly, possibly destroying civilization. The proposed study will introduce an intelligent rubber balloon that automatically acts as a water repellent to absorb the momentum of water hammers from the sea. The proposed system has been energized by wind power energy. This enables the control of the bus voltage of the DC link. Sequential balloons could be arranged in such a matter to form a repel flood wall. Wind turbine generators could be used for charging the storage batteries. These batteries energize the smart control system and DC motors coupled with air pumps. These pumps are used to inflate the sequential air balloons. The theoretical models of the proposed system components have been simulated by MATLAB environment. Three DC motors are connected based on the master-salve mechanism, and the third is considered in standby mode. These motors are controlled by a model reference adaptive controller. The tracking speed between reference and measured speeds has been accomplished. Control of switching ON-OFF balloons using fuzzy logic control and classical control has been compared. After using several control scenarios for air pressure in balloons, it is observed that the best response is obtained using fuzzy logic control since it reduces the setting time and faster time response compared to the classical PID controller. Also, it was noticed that time response improved when using a PID controller instead of proportional or PD control scenarios, and the system dynamic response became acceptable. [ABSTRACT FROM AUTHOR]

The most efficient and connected alternative for increasing the use of local renewable energy sources is a hybrid microgrid, these systems face additional challenges due to the integration of power electronics, energy storage technologies and traditional power plants. The hybrid alternating current-direct current (AC-DC) microgrid that is the subject of this research uses a primary-droop control system to regulate state variables and auxiliary services, thus, it is composed of batteries, solar panels and a miniature wind turbine (PDC) and controls how each energy source in a microgrid contributes to the final product. To achieve the given objectives, this paper will create appropriate models for each part of the microgrid design and define, among them, the energy storage batteries and power electronic converters required for each level of each of these systems. Finally, the dynamic nature of the system will be critically evaluated and characterized, to distribute the load and reduce imbalances, modify the primary drop of the resulting microgrid using MATLAB simulation. [ABSTRACT FROM AUTHOR]

In this work, we establish a fractal contact model and analyze the effect of the parameters on stress. The study provided a method to make a link between contact characteristics and surface condition. The surface texture model was built based on the process mechanism of point grinding. The experiment for the effect of the surface texture on contour height was carried out on TR300 roughness shape-measuring instrument and the structural function method of fractal theory was used to obtain the fractal dimensions and scale coefficients of surfaces with different surface textures. The fractal contact model was established based on the fractal characteristics of the surface point ground and the simulation was carried out using Matlab. Furthermore, the validation of compression experiment was carried out by WAW-600C universal testing machine, the high-definition pictures before and after the experiment were obtained by KEYENCE VH-Z500R ultra-depth-of-field 3D microscope and the surface topographies before and after the experiment were obtained by NANOVEA PS50 three-dimensional noncontact surface profile meter. The obtained findings can help to choose appropriate surface with the best contact characteristics under certain condition. [ABSTRACT FROM AUTHOR]

With the help of MATLAB numerical simulation, the motion trajectory as well as temporal and spatial radiation characteristics of high-energy electrons colliding with circularly polarized tightly focused lasers with different beam waist radii are investigated in the framework of electrodynamic and nonlinear Thomson scattering. The results reveal that the maximum amplitude of electron motion is negatively correlated with the waist radius. The spatial radiation power increases initially, followed by a decrease with the growth of the waist radius. Moreover, when the waist radius is greater than or equal to 4 times the laser wavelength ( λ 0 ), the waist radius has little effect on the electron motion trajectory and spatial radiation characteristics. The time spectrum and frequency spectrum of the laser beam with a waist radius of 4 λ 0 are analyzed. It is found that the head-on collision of a single counter-current electron with a circularly polarized laser pulse in the direction of maximum energy radiation ( φ = 2 ∘ , θ = 146. 5 ∘ ) can produce an ultra-intense pulse with attosecond duration. Moreover, we have found an optimal viewing angle range to facilitate the operation of researchers in actual experiments. [ABSTRACT FROM AUTHOR]

To keep up with the pace of renewable energy, PV Emulators are encouraged during the design and installation stages. Short circuit current, maximum power point and open circuit voltage are required to analyze the complete characteristic plot of PV panel. This paper focuses on the modeling and control of PV Emulators, as well as the comparison of the results obtained by implementing P,PI, PID and FOPID as conventional controllers with AI-based PSOPI, PSOPID and ANFIS controllers. This work will aid in minimizing time, cost and on-site constraints, allowing timely installation of PV panels after covid. Another distinguishing feature of this paper is the comparative analysis of designed models with various control strategies and their associated performance indices over complete range of PV characteristics. [ABSTRACT FROM AUTHOR]

Objective: This paper proposed a genetic fuzzy PID cascade control system. Methods: Taking the outlet temperature as the main control quantity and the inlet temperature as the secondary controlled quantity, a cascade control system was made. The genetic fuzzy PID controller was used to control the main loop, and the PI controller was used to control the secondary loop. Results: Compared with conventional PID control, the cascade genetic fuzzy PID control had the advantages of shorter regulation time, better robustness. Conclusion: The genetic fuzzy PID cascade control system for soy flour spray drying tower can improve the quality of soy flour production.

In the context of ageing, the combination of medical and health-care has become a major trend, and the introduction of the PPP model into combined medical and healthcare projects can solve the problem of lack of funds for the development of combined medical and health-care projects. Based on the evolutionary game theory, this paper constructs a three-party evolutionary game model to study the strategy choice of each party in the game process, and also analyses the evolutionary equilibrium strategy and the impact of parameter adjustment on the evolutionary strategy under different situations. The results show that the optimal solution is for the private sector to choose to provide high quality services, for the government to choose to actively regulate and for the public to choose to actively monitor. For each player, the incentives and disincentives influence their behavioural strategies. Based on the above analysis, this paper suggests establishing an independent regulator, broadening public feedback channels, and improving PPP-related laws, as well as innovating project operation methods and improving enterprise operational capabilities.

The International Water Association’s (IWA) established Anaerobic Digestion Model No. 1 (ADM1) was created to serve as a backup for experimental findings regarding the actual anaerobic digestion process. The previous model idea was adjusted and used to simulate an anaerobic digestion process in this study. Testing procedures, such as benchmark tests and balance checks, were performed in order to verify the accuracy of the implementation. These measures worked in tandem to ensure that the model was implemented flawlessly and without inconsistencies. The primary objective of this article is to construct a method that is based on the ADM1 for evaluating co-digestion and predicting the performance of the digestion process or methane yield based on the analyzed substrates’ physicochemical properties. Additional equations and simulations have been added to the standard model to create tools for evaluating the feasibility of anaerobic co-digestion. The study’s two most intriguing aspects are the optimal mixture and parameter dependence. The adjusted ADM1 is accurate in predicting the measured values of effluent COD, pH, methane, and produced biogas flows with a reasonable degree of accuracy, according to the validation results. This research shows how to use ADM1 in a wastewater treatment plant and other settings where anaerobic digestion is of interest.

Air conditioners, which have become the most widely used cooling system, have already been employed in both household and commercial environments. Automation in air conditioning is a very complex and demanding task today. When a sensor in an automatic human detection air conditioner detects the motion and activity of people, it will automatically turn on and set the temperature accordingly. However, in situations in which there are no humans around or in which human presence is unstable for an extended period, energy and power are wasted. In this regard, a control system was created utilising a Neutrosophic logic controller to regulate the AC temperature to a specific level by reducing the compressor and fan speeds without considering other parameters. Since neutrosophic logic handles the truth, ambiguity, and untruth of people in a closed environment, a more intelligent air-conditioning system is created by the suggested approach. As a result, massive quantities of energy savings are achieved. To accomplish the desired outcome, a MATLAB simulation is applied. [ABSTRACT FROM AUTHOR]

The present paper considers workspace and performance analysis of a six degree-of-freedom hexapod-type parallel manipulator with a circular guide. Compared to other similar manipulators, the design of this one allows locating all the drives fixed on the base and avoiding collisions between the carriages. The first half of the paper focuses on a procedure to determine the constant orientation (translation) workspace. The study first considers all the constraints that can affect the working area: constraints in active and passive joints, leg interference, and singularities. Next, the paper discusses the numerical procedure to construct the workspace. The proposed innovative approach combines the features of conventional geometrical and discretization methods. The suggested techniques are implemented in a MATLAB package and verified by examples with various orientations of the mechanism output link. The paper also discusses the accuracy of developed methods and mentions the required computational efforts. The second half of the work analyzes manipulator performance by calculating the conditioning index over the workspaces obtained earlier. The paper evaluates the conditioning index for an ordinary Jacobian matrix and a normalized one. In the latter case, two normalization approaches are considered: using a characteristic length and using linear velocities of three points selected on the mechanism output link. [ABSTRACT FROM AUTHOR]

Roadway excavation is the leading project in coal mining, and the cantilever roadheader is the main equipment in roadway excavation. Autonomous cutting by cantilever roadheaders is the key to realize safe, efficient and intelligent tunneling for underground roadways. In this paper, the working device of a cantilever roadheader was simplified into a series of translation or rotation joints, and the spatial pose model and spatial pose coordinate system of the roadheader were established. Using the homogeneous transformation matrix and the robot-related theory, the space pose transformation matrix of the roadheader and the space pose equation of the cutting head of the roadheader were derived. The forward kinematics and inverse kinematics of the cutting head were solved by using the D-H parameter method and an inverse transformation method. The location coordinates of the inflection point of the cutting process path for a rectangular roadway were determined, and cutting path planning and control were carried out based on the inflection point coordinates. Finally, MATLAB software was used to simulate the limit cutting area of the cutting head and the cutting process path. The simulation results showed that the limit cutting section had a bulging waist shape, the boundary around the roadway was flat, and the roadway cutting error was controlled within 1mm, which verified the reliability and effectiveness of the autonomous cutting theory of the roadheader. It lays a mathematical model and theoretical foundation for the realization of "autonomous operation of unmanned tunneling equipment". [ABSTRACT FROM AUTHOR]

The problems of additional inventory costs and inaccurate demand estimation caused by information asymmetry has severely damaged the profits of all participants and restricted the overall development of the supply chain. New technologies and ideas are urgently needed to solve these problems. The blockchain technology is widely accepted as a disruptive technology and a powerful tool to resolve information asymmetry with its advantage in decentralization, transparency, traceability, confidentiality, immutability, etc. The introduction of blockchain into the information system will effectively promote supply chain collaboration by facilitating information sharing among enterprises at various nodes. The paper builds a consortium chain model suitable for supply chain information sharing, uses evolutionary game theory to analyze the strategy changes and influencing factors in the information sharing choices of supply chain participants, and finally verifies the correctness of the results through MATLAB simulation. [ABSTRACT FROM AUTHOR]

This is the age of modern science where different kinds of gadgets are used for the betterment of humanity. Various electronic, intelligence systems are invented via modern technology where FLC (Fuzzy Logic Controller) is used to develop their intelligence systems. Nowadays, FLC is widely used in uncertainty and robust development systems. Two inputs and one output have been used in this paper. Also, various defuzzification methods are used to determine the washing time of a smart washing machine. Finally, the performance of the various defuzzification methods has been compared mathematically. This work has been simulated by using the MATLAB toolbox. [ABSTRACT FROM AUTHOR]

To ensure the cutting speed during the cutting operation, this paper proposes a groove cutting speed inference planning system that relies on production experience and set parameters and is based on machine vision and a two-level fuzzy neural hybrid network. The overall structure of the inference system is designed, including the mechanical body, vision system, and fuzzy neural hybrid network. The contour information of the part is obtained using industrial cameras and digital image processing systems. The cutting speed of the trajectory segment is inferred based on the related processing parameters and the secondary fuzzy neural hybrid network. Finally, all of the processing parameters are transmitted to the PLC, so that the robot can work according to the predetermined displacement and speed. Simulations verify that the speed inference planning system offers certain advantages compared to the traditional one. The appearance of the speed inference planning realises independent design and planning of the cutting speed, and further ensures the unity of the cutting quality and cutting speed. This proposed method provides a new direction for the development and transformation of machining processes that rely on manual experience and in which expert systems cannot be used. [ABSTRACT FROM AUTHOR]