Enhancing the Efficiency of Multi-Electrolyzer Clusters with Lye Mixer:Topology Design and Control Strategy

The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers.These setups present various operational modes:independent operation and multi-electrolyzer parallelization,each with distinct advantages and challenges.This study introduces an innovative configuration that incorporates a mutual lye mixer among electrolyzers,establishing a weakly coupled system that combines the advantages of two modes.This approach enables efficient heat utilization for faster hot-startup and maintains heat conservation post-lye interconnection,while preserving the option for independent operation after decoupling.A specialized thermal exchange model is developed for this topology,according to the dynamics of the lye mixer.The study further details startup procedures and proposes optimized control strategies tailored to this structural design.Waste heat from the caustic fully heats up the multiple electrolyzers connected to the lye mixing system,enabling a rapid hot start to enhance the system’s ability to track renewable energy.A control strategy is established to reduce heat loss and increase startup speed,and the optimal valve openings of the diverter valve and the manifold valve are determined.Simulation results indicate a considerable enhancement in operational efficiency,marked by an 18.28%improvement in startup speed and a 6.11%reduction in startup energy consumption inmulti-electrolyzer cluster systems,particularlywhen the systems are synchronized with photovoltaic energy sources.The findings represent a significant stride toward efficient and sustainable hydrogen production,offering a promising path for large-scale integration of renewable energy.

Research on the Control Strategy of Micro Wind-Hydrogen Coupled System Based on Wind Power Prediction and Hydrogen Storage System Charging/Discharging Regulation

This paper addresses the micro wind-hydrogen coupled system,aiming to improve the power tracking capability of micro wind farms,the regulation capability of hydrogen storage systems,and to mitigate the volatility of wind power generation.A predictive control strategy for the micro wind-hydrogen coupled system is proposed based on the ultra-short-term wind power prediction,the hydrogen storage state division interval,and the daily scheduled output of wind power generation.The control strategy maximizes the power tracking capability,the regulation capability of the hydrogen storage system,and the fluctuation of the joint output of the wind-hydrogen coupled system as the objective functions,and adaptively optimizes the control coefficients of the hydrogen storage interval and the output parameters of the system by the combined sigmoid function and particle swarm algorithm(sigmoid-PSO).Compared with the real-time control strategy,the proposed predictive control strategy can significantly improve the output tracking capability of the wind-hydrogen coupling system,minimize the gap between the actual output and the predicted output,significantly enhance the regulation capability of the hydrogen storage system,and mitigate the power output fluctuation of the wind-hydrogen integrated system,which has a broad practical application prospect.

Path Planning and Tracking Control for Parking via Soft Actor-Critic Under Non-Ideal Scenarios

Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.

Model Predictive Control Strategy of Multi-Port Interline DC Power Flow Controller

There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power grid.In recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability.This work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance.Initially,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control objectives.Sub module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC strategy.Finally,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

Simulation Study of the Control Strategy of a DC Inverter Heat Pump Using a DC Distribution Network

Photovoltaics,energy storage,direct current and flexibility(PEDF)are important pillars of achievement on the path to manufacturing nearly zero energy buildings(NZEBs).HVAC systems,which are an important part of public buildings,play a key role in adapting to PDEF systems.This research studied the basic principles and operational control strategies of a DC inverter heat pump using a DC distribution network with the aim of contributing to the development and application of small DC distribution systems.Along with the characteristics of a DC distribution network and different operating conditions,a DC inverter heat pump has the ability to adapt to changes in the DC bus voltage and adds flexibility to the system.Theoretical models of the DC inverter heat pump integrated with an ice storage unit were developed.The control strategies of the DC inverter heat pump system considered the influence of both room temperature and varied bus voltage.A simulation study was conducted using MATLAB&Simulink software with simulation results validated by experimental data.The results showed that:(1)The bus fluctuation under the rated working voltage had little effect on the operation of the unit;(2)When the bus voltage was fluctuating from 80%-90%or 105%-107%,the heat pump could still operate normally by reducing the frequency;(3)When the bus voltage was less than 80%or more than 107%,the unit needed to be shut down for the sake of equipment safety,so that the energy storage device could adjust to the sharp decrease or rise of voltage.

Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking

This paper develops a novel hierarchical control strategy for improving the trajectory tracking capability of aerial robots under parameter uncertainties.The hierarchical control strategy is composed of an adaptive sliding mode controller and a model-free iterative sliding mode controller(MFISMC).A position controller is designed based on adaptive sliding mode control(SMC)to safely drive the aerial robot and ensure fast state convergence under external disturbances.Additionally,the MFISMC acts as an attitude controller to estimate the unmodeled dynamics without detailed knowledge of aerial robots.Then,the adaption laws are derived with the Lyapunov theory to guarantee the asymptotic tracking of the system state.Finally,to demonstrate the performance and robustness of the proposed control strategy,numerical simulations are carried out,which are also compared with other conventional strategies,such as proportional-integralderivative(PID),backstepping(BS),and SMC.The simulation results indicate that the proposed hierarchical control strategy can fulfill zero steady-state error and achieve faster convergence compared with conventional strategies.

Prevention and Control Strategies of Nosocomial Infection and Effectiveness Evaluation in a Tertiary Teaching Hospital during the Epidemic of COVID-19

Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.

Analysis of Hospital Budget Management Control Based on Smart Hospital

Hospitals are crucial healthcare facilities where patients seek treatment,and effective budget management within hospitals significantly impacts their operational efficiency and financial performance.In the age of information technology and advanced healthcare solutions,the emergence of smart hospitals represents a new trend in the medical industry’s evolution.Leveraging modern information technology can enhance the development of hospital IT systems and drive budget management toward greater intelligence.This paper begins by analyzing the influence of smart hospitals on hospital budget control.It then examines the current state of budget management control within smart hospitals.Finally,it proposes several strategies for budget management control in smart hospitals,aiming to provide guidance for relevant stakeholders.

Optimization of Sporulation Conditions of Biocontrol Bacteria B579 by Two-step Control Strategy

[Objective] For preparing the biopesticide of Bacillus subtilis B579 with high spore concentration,the sporulation conditions were optimized.[Method] Two-step fermentation control strategy was used,in which,the first phase（0-10 h）was to improve cell growth,and the second phase（10-30 h）was to promote spore formation.Four factors including initial glucose concentration,fermentation pH,temperature（in the second phase）and shaking speed（in the second phase）were optimized using the methods of single factor test and orthogonal experiment.[Result] The initial glucose concentration showed a significant effect on sporulation.The optimal conditions for the spore formation of B.subtilis B579 were as follows：initial glucose concentration 5 g/L,fermentation pH 7.0,the temperature for the first phase 37 ℃,and the shaking speed for the first phase 180 r/min,the temperature for the second phase 40 ℃,and the shaking speed for the second phase 200 r/min;in addition,the first phase was 10 h and the second phase of fermentation was conducted for 30 h.Under such conditions,the spore concentration and spore formation rate could reach 9.43×108 CFU/ml and 90.99%,respectively,which represented 6.70-fold and 2.43-fold increase compared with those before optimization.[Conclusion] The spores concentration of biocontrol agent was improved using two-step control strategy,which provided the basis for biopesticide production in large scale.

Series-parallel Hybrid Vehicle Control Strategy Design and Optimization Using Real-valued Genetic Algorithm

Despite the series-parallel hybrid electric vehicle inherits the performance advantages from both series and parallel hybrid electric vehicle, few researches about the series-parallel hybrid electric vehicle have been revealed because of its complex co nstruction and control strategy. In this paper, a series-parallel hybrid electric bus as well as its control strategy is revealed, and a control parameter optimization approach using the real-valued genetic algorithm is proposed. The optimization objective is to minimize the fuel consumption while sustain the battery state of charge, a tangent penalty function of state of charge（SOC） is embodied in the objective function to recast this multi-objective nonlinear optimization problem as a single linear optimization problem. For this strategy, the vehicle operating mode is switched based on the vehicle speed, and an ＂optimal line＂ typed strategy is designed for the parallel control. The optimization parameters include the speed threshold for mode switching, the highest state of charge allowed, the lowest state of charge allowed and the scale factor of the engine optimal torque to the engine maximum torque at a rotational speed. They are optimized through numerical experiments based on real-value genes, arithmetic crossover and mutation operators. The hybrid bus has been evaluated at the Chinese Transit Bus City Driving Cycle via road test, in which a control area network-based monitor system was used to trace the driving schedule. The test result shows that this approach is feasible for the control parameter optimization. This approach can be applied to not only the novel construction presented in this paper, but also other types of hybrid electric vehicles.

An Optimal Control Strategy for Multi-UAVs Target Tracking and Cooperative Competition

An optimal control strategy of winner-take-all(WTA)model is proposed for target tracking and cooperative competition of multi-UAVs(unmanned aerial vehicles).In this model,firstly,based on the artificial potential field method,the artificial potential field function is improved and the fuzzy control decision is designed to realize the trajectory tracking of dynamic targets.Secondly,according to the finite-time convergence high-order differentiator,a double closed-loop UAV speed tracking the controller is designed to realize the speed control and tracking of the target tracking trajectory.Numerical simulation results show that the designed speed tracking controller has the advantages of fast tracking,high precision,strong stability and avoiding chattering.Finally,a cooperative competition scheme of multiple UAVs based on WTA is designed to find the minimum control energy from multiple UAVs and realize the optimal control strategy.Theoretical analysis and numerical simulation results show that the model has the fast convergence,high control accuracy,strong stability and good robustness.

Fuzzy-immune control strategy of a hydro-viscous soft start device of a belt conveyor

Considering the control difficulties of a hydro-viscous trol algorithm was derived. A fuzzy-immune PID controller was soft start （HVSS） device of a belt conveyor, a fuzzy-immune con- designed based on immune feedback regulations and adaptability of the fuzzy logic inference. Using MATLAB software, we simulated the controller and compared the HVSS device with a conven- tional PID controller and a fuzzy PID controller. The simulation results show that the controller is not only very reliable as a PID controller, robust and requires only a short adjustment time of fuzzy control, but possesses also capacity of global optimization of the immune algorithm. To verify our theoretical analysis and simulation, a HVSS test-bed was developed. The experimental results demonstrate that the fuzzy-immune PID controller managed to start the belt conveyor softly and to follow an S-shaped curve while the output speed correctly followed the preset speed with only small fluctuations in speed.

Coordinate control strategy for stability operation of offshore wind farm integrated with Diode-rectifier HVDC

Due to low investment cost and high reliability,a new scheme called DR-HVDC(Diode Rectifier based HVDC)transmission was recently proposed for grid integration of large offshore wind farms.However,in this scheme,the application of conventional control strategies for stability operation face several challenges due to the uncontrollability of the DR.In this paper,a coordinated control strategy of offshore wind farms using the DR-HVDC transmission technology to connect with the onshore grid,is investigated.A novel coordinated control strategy for DR-HVDC is proposed based on the analysis of the DC current control ability of the full-bridge-based modular multilevel converter(FB-MMC)at the onshore station and the input and output characteristics of the diode rectifier at the offshore.Considering the characteristics of operation stability and decoupling between reactive power and active power,a simplified design based on double-loop droop control for offshore AC voltage is proposed after power flow and voltage–current(I–V)characteristics of the offshore wind farm being analyzed.Furthermore,the impact of onshore AC fault to offshore wind farm is analyzed,and a fast fault detection and protection strategy without relying on communication is proposed.Case studies carried out by PSCAD/EMTDC verify the effectiveness of the proposed control strategy for the start up,power fluctuation,and onshore and offshore fault conditions.

Ground-Based Hyperspectral Stereoscopic Remote Sensing Network: A Promising Strategy to Learn Coordinated Control of O_(3) and PM_(2.5) over China

With the coming of the“14th Five-Year Plan,”the coordinated control of particulate matter with an aerodynamic diameter no greater than 2.5 lm(PM_(2.5))and O_(3) has become a major issue of air pollution prevention and control in China.The stereoscopic monitoring of regional PM_(2.5) and O_(3) and their precursors is crucial to achieve coordinated control.However,current monitoring networks are currently inadequate for monitoring the vertical profiles of both PM_(2.5) and O_(3) simultaneously and support air quality control.The University of Science and Technology of China(USTC)has established a nationwide ground-based hyperspectral stereoscopic remote sensing network based on multi-axis differential optical absorption spectroscopy(MAX-DOAS)since 2015.This monitoring network provides a significant opportunity for the regional coordinated control of PM_(2.5) and O_(3) in China.One-year vertical profiles of aerosol,NO_(2) and HCHO monitored from four MAX-DOAS stations installed in four megacities(Beijing,Shanghai,Shenzhen,and Chongqing)were used to characterize their vertical distribution differences in four key regions,Jing–Jin–Ji(JJJ),Yangtze River Delta(YRD),Pearl River Delta(PRD),and Sichuan Basin(SB),respectively.The normalized and yearly averaged aerosol vertical profiles below 400 m in JJJ and PRD exhibit a box shape and a Gaussian shape,respectively,and both show exponential shapes in YRD and SB.The NO_(2) vertical profiles in four regions all exhibit exponential shapes because of vehicle emissions.The shape of the HCHO vertical profile in JJJ and PRD was Gaussian,whereas an exponential shape was shown in YRD and SB.Moreover,a regional transport event occurred at an altitude of 600–1000 m was monitored in the southwest–northeast pathway of the North China Plain(NCP)by five MAX-DOAS stations(Shijiazhuang(SJZ),Wangdu(WD),Nancheng(NC),Chinese Academy of Meteorological Sciences(CAMS),and University of Chinese Academy of Sciences(UCAS))belonging to the above network.The aerosol optical depths(AOD)in these five stations decreased in the order of SJZ>WD>NC>CAMS>UCAS.The short-distance regional transport of NO2 in the 700–900 m layer was monitored between WD and NC.As an important precursor of secondary aerosol,the peak of NO_(2) air mass in WD and NC all occurred 1 h earlier than that of aerosol.This was also observed for the short-distance regional transport of HCHO in the 700–900 m layer between NC and CAMS,which potentially affected the O_(3) concentration in Beijing.Finally,CAMS was selected as a typical site to determine the O_(3)–NO_(x)–volatile organic compounds(VOCs)sensitivities in vertical space.We found the production of O_(3) changed from predominantly VOCs-limited conditions to mainly mixed VOCs–NO_(x)-limited condition from the 0–100 m layer to the 200–300 m layer.In addition,the downward transport of O_(3) could contribute to the increase of ground surface O_(3) concentration.This ground-based hyperspectral stereoscopic remote sensing network provide a promising strategy to support management of PM_(2.5) and O_(3) and their precursors and conduct attribution of sources.

Integrated Control Strategy for CVT Powertrains with Consideration of Vehicle Drivability

During shift,power flow is not interrupted in powertrains equipped with continuously variable transmission（CVT）.When hard acceleration is commanded,engine speed will flare and corresponding torque will be consumed,which leads to a drop in vehicle drive torque and also the vehicle acceleration.This is the reason why CVT vehicles have poor drivability during hard acceleration maneuver.Conventional method such as torque compensation doesn＇t always work due to the limited backup torque of engine.According to this,means to evaluate the drivability of CVT vehicles are studied,affect factors of drivability are analyzed in detail.Hard acceleration process of CVT vehicle is studied by theoretical analysis,based on which engine torque and ratio change rate of CVT are identified as two key control parameters that decide the drivability of CVT vehicles during hard acceleration maneuver.Therefore,a control strategy based on restricting the change rate of CVT ratio together with torque compensation is proposed,and two different algorithms to establish the limitation of ratio change rate are proposed.These two algorithms are simulated and compared with each other,results indicate that drop of vehicle acceleration is eliminated evidently by limit the change rate of CVT ratio,but small ratio change rate also results in a longer time to finish the accelerate process,an algorithm to decide a proper ratio change rate is needed in order to tune these different characteristics.In order to get better control effects,a new fuzzy logic based algorithm is proposed to decide a proper ratio change rate during kick down conditions,simulation and experiment results indicate that,the amount of vehicle acceleration decrease is reduced from about 1 m/s2 to almost 0,in the mean time the accelerate process only delayed for about 0.3 s.The proposed control strategy and algorithm can effectively tune the characteristics of CVT equipped vehicle during kick down conditions.

Control strategy of shortcut nitrification

Shortcut nitrification for ammonium-rich wastewater is energy-saving and cost-effective procedure that has become one of the hotspots in the field of biological denitrogenation. An orthogonal experiment was performed to study the combined effects of operational parameters on the performance of internal-loop airlift bioreactor for shortcut nitrification. The optimum operational parameters for the shortcut nitrification were fotmd as temperature 35 ℃, pH 8.0, dissolved oxygen concentration 1.0 mg/L, ammonium concentration 4 mmol/L and HRT 16 h, which have different influence on the performance of shortcut nitrification reactor. The pH, temperature and dissolved oxygen concentration have significant bearing on the process. The results showed that the shortcut nitrification reactor could be successfully started up within 42 d, and the reactor performance is steady with minimum NO2-/NOx- of 85.2%, maximum 93.4% and average value of 91.4% in effluent. Based on the analysis of experimental data, a new control strategy named “priority ＋ combination” for shortcut nitrification was suggested. Through this strategy, the startup and operation of shortcut nitrification for ammonium-rich sludge digester liquids were optimized. The control strategy works well to keep the reactor operation in steady state and in achieving high-efficiency for shortcut nitrification.

Study on Steering Control Strategy for High-Speed Tracked Vehicle with Hydrostatic Drive

Steering control strategy for high-speed tracked vehicle with hydrostatic drive is designed based on analyzing the fundamental steering theories of the hydrostatic drive tracked vehicle. The strategy is completed by the cooperation between integrated steering control unit and pump ＆ motor displacement controller. The steering simulation is conducted by using Simulink of Matlab. It is indicated that this steering control strategy can reduce the average vehicle speed automatically to achieve the driver＇s expected steering radius exactly in the case of en- suring not exceeding the system pressure threshold and no sideslip.

Simulation and control strategy for the variational influent of WWTP

With the development of activated sludge model, the simulation software for the design and operation of wastewater treatment plant （WWTP） was produced and has been widely used. The dynamic change of the quality and flow of influent are major factors causing the unstable operation of wastewater treatment process. As a basic model, ASMI model was used for the simulation of activated sludge process, and double exponential model was selected for the simulation of secondary sedimentation tank. The influences of influent change to the aeration tank and secondary sedimentation tank were investigated, and the relationship among influent change, the quality of effluent and the level of sludge blanket in secondary sedimentation tank was established. On the basis of the simulation results, the operation of the WWTP could be adjusted under the dynamic change of the influent. Furthermore, the controlling strategy combined the feed-forward on the influent flow and the feedback on the level of sludge blanket in the secondary sedimentation tank was studied.

Mode switching control strategy of dual motors coupled driving on electric vehicles

Based on analyzing the structure and working principle on electric vehicles （EVs） with dual motors coupled by planetarY gears, the control strategy of mode switching was proposed. The power interruption problem on EVs with automatic mechanical transmission （AMT） shifting was resolved. Based on the speed-torque characteristics of the planetary gears and the principle of the auxiliary motor＇ s zero speed braking, control features of mode switching were introduced. The mode shifting between the main motor mode and dual motors coupled driving were studied. Matlab/Simulink was adopted as a platform to develop the simulation model of EVs with dual motors drive system and 3 gears AMT. Simulation results demonstrated that the power interruption of dual motors drive system was solved during mode switching. The power requirements of EVs were satisfied, too.