Search

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. [ABSTRACT FROM AUTHOR]

In view of the problems such as too many times of rejected tasks and waste of resources in fault - tolerant fair scheduling FT-FS(Fault Tolerate Fair Scheduler) algorithm, a new fair scheduling algorithm PA - FTFS (Primary Alternate and Fault Tolerant Fair Scheduling) is proposed based on FT-FS algorithm by integrating the main/alternative PA (Primary Alternate) fault-tolerant strategy. This algorithm can reduce the number of rejected tasks in multi core processor system and reduce the waste of resources. MATLAB simulation software is used to verify the above algorithms. The experimental results show that PA-FTFS algorithm using proportional replacement task strategy has significantly reduced the number of task rejection times compared with FT - FS algorithm after permanent kernel failure. Data analysis shows that PA-FTFS algorithm has better failure rate and scheduling rate than FT-FS algorithm. [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.

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]

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]

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]

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.

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Considering the fact that ships at sea will be affected by waves, sea breeze and air currents, which usually results in serious interference of equipment that needs to work in a stable environment, such as lifting platforms, radar signal capture, etc. In response to the above problems, the S-RPS-SPS parallel mechanism is established to stabilize the platform. It can realize the roll angle of the rotation around the X axis and the pitch angle of rotation around the Y axis; it can also indirectly eliminate the rotation of the hull on these two axes. Model this parallel mechanism in Solidworks software and verify the degrees of freedom. The relation between the length of two driving rods and the pose angle of the moving platform is calculated by the method of inverse pose solution. Two sets of data are obtained by inputting different angles in the range of the rotating angle of the moving platform and the expansion length of the driving rod. The calculation formula, rotation angle range and coordinates are simulated by algorithms in Matlab software, and the correctness of the moving platform pose is verified. The simulation results show that the accuracy and reliability of this mechanism in terms of kinematics are well guaranteed.

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]

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.

In view of the traditional agricultural irrigation in hills and mountains, which usually uses artificial control solenoid valve for irrigation, the problems of water waste and high labor cost has come into being. A set of automatic irrigation control system based on fuzzy control and PID control is designed. The stability of PID control and adaptability of fuzzy control are combined to control irrigation time. The irrigation system of hills and mountains built by Simulink is controlled by conventional PID and fuzzy PID respectively. The simulation experiments show that compared with the conventional PID control, the fuzzy PID control system has significantly reduced overshoot and adjustment time, and has higher stability, adaptability and adjustment performance. It can be used in the automatic irrigation system of hilly and mountainous agriculture. [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]

Background The escalating global population, surpassing seven billion in 2012, amplifies the strain on existing resources for food, housing, and conventional energy. Addressing these challenges requires the development of economically and environmentally viable renewable energy technologies. Photovoltaic (PV) solar modules stand out for their eco-friendly operation and reliability. In off-grid communities, stand-alone PV systems, coupled with battery storage, play a pivotal role in meeting electrical energy needs. Methods This study enhances the understanding of stand-alone PV systems through modeling and simulation using MATLAB software. A multi-crystalline PV system, specifically the Kyocera KC130GT, is investigated under varying conditions, and a pulse width modulation (PWM) controller is employed for battery charging. Results The study reveals profound effects on energy production based on the I-V and P-V characteristics of the modeled system when a PWM controller is utilized. The system demonstrates successful energy generation under different conditions, accounting for temperature variations and PV battery voltage mismatches. Conclusion The simulated model serves as a versatile system capable of detecting different conditions in varying light and temperature scenarios. Effective temperature monitoring, voltage adjustment using a suitable charger controller, and the selection of optimal materials for solar modules can significantly enhance the system’s efficiency. The results emphasize the importance of careful consideration of PV system sizing corresponding to battery capacity for improved solar system efficiency. While the cost of the modeled stand-alone PV system is currently low, scalability to larger projects may incur increased costs due to the high prices of photovoltaic panels, batteries, and other components.

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.

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 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]

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]

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.

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 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]

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.

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.

A series of problems such as low accuracy, poor reliability, and difficulty in operation caused by the performance test of conventional battery discharge using variable resistors. A battery performance test method for grid-connected charging and discharging is proposed. Through the analysis of the differential expressions of charge, temperature and current in lead-acid batteries, a third-order equivalent mathematical model composed of the main reaction branch and parasitic branch is established. The charge and discharge of the battery use a step signal to trigger Buck-Boost bidirectional In the constant current mode of the switch of the conversion circuit, the inverter circuit adopts voltage and current double closed-loop control and is filtered by inductance and merged into the analog power grid. A simulation model was built on MATLAB/Simulink software, and the research results showed that the various performance indicators of the battery and the grid-connected current dynamic response are good, which reflects the effectiveness and environmental protection of the research method. [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]

Background A photovoltaic (PV) system, especially the stand-alone type, along with a battery storage system, plays a significant role in providing the needed electrical energy to remote, off-grid communities. Methods In this study, a stand-alone PV solar cell was enhanced to better understand the system operation. Modeling and simulation were performed using MATLAB software. Results This work has shown that the I-V (current-voltage) and P-V (power-voltage) characteristics of the modelled system have a profound effect on energy when a pulse width modulation controller is used as a charger. The modelled PV system generated the required energy under different conditions, considering temperature and PV battery voltage mismatches. Conclusion In summary, the simulated model in this study can be considered a system capable of detecting different conditions with the presence or absence of light at different temperatures. Finally, monitoring the temperatures, adjusting the voltage with a suitable charger controller, and selecting solar modules made of optimal materials can increase the efficiency of the solar system and allow it to be used in more applications.

Taking the hydraulic follow-up arm of a company as the research object， an improved D-H coordinate system is established， and a 3D workspace of the end-effector of the hydraulic follow-up arm is solved by the forward kinematics equation. Based on Monte Carlo method and extreme value theory， the working face at the height of fracturing wellhead is solved， and the influence of the arm length of hydraulic servo arm on the stopping distance and working width is studied under the condition of fixed stopping error. The results show that， under the fixed stopping error， when the current arm length is greater than or equal to the rear arm length， with the extension of the front arm of the hydraulic follow-up arm， the equal slope of the stopping distance increases， and the working width is basically stays unchanged. With the extension of the large arm after the hydraulic follow-up arm， the parking distance is basically stays unchanged， but the slope such as the working width becomes wider. On this basis， a reasonable interface height is proposed to alleviate the large difference between the two arms. The research results can provide theoretical reference for the optimization design of the hydraulic follow-up arm.

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]

In traditional VSG control, the introduction of the inertia moment and damping coefficient of the synchronous generator into the photovoltaic inverter will result in poor dynamic adjustment capabilities of the photovoltaic grid-connected system. In view of this problem, this study proposes an improved VSG control strategy. The relationship between power angle and active power and the transient process of the rotor angular frequency oscillation period are discussed through the mathematical model of the converter. The principles for selecting moment of inertia and damping coefficient are given, and the rate of change of moment of inertia and angular frequency as well as damping coefficient and angular frequency are analyzed. The relationship between the changes leads to the improvement strategy of photovoltaic grid-connected under the control of adaptive VSG. The simulation results show that the photovoltaic grid-connected system based on the adaptive VSG control strategy has a good dynamic response, which proves the effectiveness and superiority of the improved strategy. [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]

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 overcome the lack of robustness of the nonlinear dynamic inversion (NDI) control, a simple and practical adaptive NDI control method based on an improved piecewise constant is proposed in this paper to enhance its robustness to disturbances and improve the accuracy of response tracking. Firstly, reasonable assumptions and analyses are made for the system with the influence of disturbance. Secondly, an improved piecewise constant adaptive NDI control method suitable for general flight control systems is proposed. The stability of the control system with disturbance and the error convergence range of the improved piecewise constant adaptive control are proved and analyzed theoretically. Finally, taking into account the fighter actual control requirements, the angular rates control strategy is given, and the proposed method is applied to the angular rates flight controller design. Matlab simulations are carried out under the disturbance of the actuator failure and the sudden change of the center of gravity, and the robustness and dynamic performance of the controller designed based on the present method is compared and verified. The results illustrate that our present method has stronger robustness and higher control accuracy.

This article presents the velocity and singularity analysis for a five-degree-of-freedom (5-DOF) parallel-serial manipulator. The hybrid structure of the manipulator combines a tripod-like parallel part and a serial part, represented as two carriages moving in perpendicular directions. This manipulator provides its end-effector with a 3T2R motion pattern, which includes three independent translations and two independent rotations. First, the study briefly discusses the manipulator design and the results of the position analysis. These results form the basis for the subsequent velocity and singularity analysis, performed by screw theory. The screw coordinates of the unit twists are written for each manipulator joint, and then through the reciprocal screw approach, the actuation and constraint wrenches of the manipulator are obtained by simple inspection. Based on these twists and wrenches, the paper forms the velocity equation and shows an example of the inverse velocity analysis for a given end-effector trajectory. The same example is solved by numerical differentiation to verify the proposed approach. Next, the paper investigates singular configurations by analyzing the wrench system of the manipulator and presents several conditions for serial and parallel singularities. Each condition has both a symbolic representation, given by an equation for screw coordinates of certain wrenches, and a visual representation, which shows the manipulator in a singular configuration. [ABSTRACT FROM AUTHOR]

Nowadays pollution and greenhouse gasses emissions led to the definition of action plans and guidelines aimed at improving renewable power production and circular & green economy approaches. Anaerobic digestion of organic wastes represents a meeting point between circular economy and bioenergy exploitation. The huge variety of residual biomass materials for anaerobic digestion makes clear the importance of the simulation process to underline biogas production and critical operating plant conditions for each kind of processed substrate and used reactors. Main target of this work is the definition of a software tool, called ADMS 1.0 (Anaerobic Digestion Model Simulator version 1.0), by which the user can conduct both implementation and simulation of anaerobic digestion biochemical processes (continuous-flow stirred tank reactors and batch reactors). This software tool is composed by an ad-hoc graphic user interface (GUI) developed in Python and a computing core, written in MATLAB. Anaerobic Digestion Model N.1 (ADM1) was implemented. Two simulations were carried out implementing the same scenario both in AQUASIM and ADMS 1.0 to validate the correct functioning and numerical consistency of the proposed tool. The scenario is based on experimental data. The results obtained by both software tools were compared to confirm the consistency of numerical outputs. Differences between these results have been measured by the introduction of a mean of the relative errors associated to the singular simulated biochemical component. This error, expressed in percentage, represents the discrepancy between AQUASIM and ADMS 1.0 results. The relative errors average value is equal to 0.0648%, which is consistently less than the acceptable engineering value of 5%.

In this study, a fractional order proportional integral derivative (FOPID) controller is designed to create the reference power trajectory and to conquer the uncertainties and external disturbances. A fractional nonlinear model was utilized to describe the nuclear reactor dynamic behaviour considering thermal-hydraulic effects. The controller parameters were tuned using optimization method in Matlab/Simulink. The FOPID controller was simulated using Matlab/Simulink and the controller performance was evaluated for Hard variation of the reference power and compared with that of integer order a proportional integral derivative (IOPID) controller by two models of fractional neutron point kinetic (FNPK) and classical neutron point kinetic (CNPK). Also, the FOPID controller robustness was appraised against the external disturbance and uncertainties. Simulation results showed that the FOPID controller has the faster response of the control attempt signal and the smaller tracking error with respect to the IOPID in tracking the reference power trajectory. In addition, the results demonstrated the ability of FOPID controller in disturbance rejection and exhibited the good robustness of controller against uncertainty.

The detailed model of the back-to-back converter of the permanent magnet direct drive wind power system contains multiple power electronic devices, and the use of pulse width modulation technology will inevitably increase the mathematical calculation of the simulation system. In view of the problem, a mean value model is proposed to simplify the system so that the wind power system can operate quickly and stably. For the converter mean value model, the controlled power supply is used to replace the converter in structure, and its higher harmonics are ignored in principle, and only the fundamental wave component is retained. In addition, from the perspective of system control, the control strategy of the system is improved by removing the PWM modulation process. Finally, a permanent magnet direct drive wind power system simulation model is built in MATLAB/Simulink, and the system response of the mean model and the detailed model are compared. The simulation results show that the mean value model can not only meet the system accuracy requirements, but also speed up the system simulation speed, greatly improve the system stability, which verifies the rationality of the control strategy. [ABSTRACT FROM AUTHOR]

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)