Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybr...Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.展开更多
Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exa...Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exacerbates this challenge by rendering the process vulnerable to environmental changes and unexpected factors,resulting in defects and inconsistent product quality,particularly in unmanned long-term operations or printing in extreme environments.To address these issues,we developed a process monitoring and closed-loop feedback control strategy for the 3D printing process.Real-time printing image data were captured and analyzed using a well-trained neural network model,and a real-time control module-enabled closed-loop feedback control of the flow rate was developed.The neural network model,which was based on image processing and artificial intelligence,enabled the recognition of flow rate values with an accuracy of 94.70%.The experimental results showed significant improvements in both the surface performance and mechanical properties of printed composites,with three to six times improvement in tensile strength and elastic modulus,demonstrating the effectiveness of the strategy.This study provides a generalized process monitoring and feedback control method for the 3D printing of continuous fiber-reinforced composites,and offers a potential solution for remote online monitoring and closed-loop adjustment in unmanned or extreme space environments.展开更多
The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to ...The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
Additive manufacturing(AM)promotes the production of metallic parts with significant design flexibility,yet its use in critical applications is hindered by challenges in ensuring consistent quality and performance.Pro...Additive manufacturing(AM)promotes the production of metallic parts with significant design flexibility,yet its use in critical applications is hindered by challenges in ensuring consistent quality and performance.Process variability often leads to defects,insufficient geometric accuracy and inadequate material properties,which are difficult to effectively manage due to limitations of traditional quality control methods in modeling highdimensional nonlinear relationships and enabling adaptive control.Machine learning(ML)offers a transformative approach to model intricate process-structure-property relationships by leveraging the rich data environment of AM.The study presents a comprehensive examination of ML-driven quality assurance implementations in metallic AM.First,it uniquely examines the innovative exploration of ML in predicting and understanding the fundamental multi-physics fields that influence the quality of a fabricated component,including temperature fields,fluid dynamics and stress/strain evolution.Subsequently,the application of ML in optimizing key quality attributes,including defect detection and mitigation(porosity,cracks,etc.),geometric fidelity enhancement(dimensional accuracy,surface roughness,etc.)and material property tailoring(mechanical strength,fatigue life,corrosion resistance,etc.),are discussed in detail.Finally,the development of ML-driven real-time closed-loop control systems for intelligent quality assurance,the strategies for addressing the data scarcity and cross-scenario transferability in metal AM are discussed.This article provides a novel perspective on the profound potential of ML technology for metal AM quality control applications,highlights the challenges faced during research,and outlines future development directions.展开更多
This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
The high necessity to develop novel and optimized technologies for crop production is very high due to the exponential growth in term of world population of the last years.In this field a novel use of fertilizers and ...The high necessity to develop novel and optimized technologies for crop production is very high due to the exponential growth in term of world population of the last years.In this field a novel use of fertilizers and pesticides can ameliorate the life conditions around the world due to the higher productivity with lower losses and consequent less environmental problems related to pollution.To address these challenges a very promising solution is constituted by devices able to control and sustain the release of fertilizers and pesticide optimizing their efficacy preserving the environment.In the last decade a lot of efforts,in terms of research,were dedicated to the development of smart devices that can address those issues maintaining also low costs and easy production processes.In this review we will point the attention on devices that can be used as slow release systems for fertilizers and/or pesticides.In details strong consideration will be devoted to their formulation to increase the knowledge on the high number of possibilities behind these novel and smart devices.展开更多
Gualou-Xiebai-Banxia Decoction(GXBD)is a traditional Chinese herbal formula including four traditional Chinese medicines:Gualou(Trichosanthis Fructus,TF),Xiebai(Allii Macrostemonis Bulbus,AMB),Banxia(Pinelliae Rhizoma...Gualou-Xiebai-Banxia Decoction(GXBD)is a traditional Chinese herbal formula including four traditional Chinese medicines:Gualou(Trichosanthis Fructus,TF),Xiebai(Allii Macrostemonis Bulbus,AMB),Banxia(Pinelliae Rhizoma,PR)and yellow wine.It is a classical therapy for chest stuffiness and pain syndrome and is widely used in the clinical treatment of coronary heart disease.It also shows significant therapeutic effects on pulmonary heart disease,hyperlipidemia,and arrhythmia.This study conducted a literature review and collected information on GXBD from databases such as PubMed,Web of Science,China National Knowledge Infrastructure,and ScienceDirect.The result indicated that the main active ingredients of GXBD are steroids,flavonoids,terpenoids,alkaloids,amino acids,and organic acids.Trigonelline,macrostemonoside and cucurbitacin B can provide reference for its quality control.GXBD may exert therapeutic effects on coronary heart disease through AMPK,PI3K-AKT,oxLDL,VEGF,and NF-κB signal pathways.This review provides a comprehensive analysis and summary of the chemical composition and in vivo metabolism of three traditional Chinese medicines(TF,AMB,and PR),along with an evaluation of the chemical composition,quality control,pharmacological effects,and clinical application of GXBD.Based on these,areas requiring further research on GXBD have been proposed to provide a reference for its further development and new drug research.展开更多
Radionuclide imaging is divided into positron emission tomography and single photon emission tomography and is widely used in clinical practice for diagnosis and treatment,as well as in clinical research for the devel...Radionuclide imaging is divided into positron emission tomography and single photon emission tomography and is widely used in clinical practice for diagnosis and treatment,as well as in clinical research for the development and evaluation of new therapies.Although it is a visually intuitive form of three-dimensional functional imaging,this modality requires the injection of radiopharmaceuticals labeled with positron-or gamma-emitting isotopes into patients to assess and quantify anabolism,gene expression,and other processes.For this reason,radiopharmaceuticals must undergo rigorous quality control(QC)to ensure product purity,efficacy,and safety.Traditional QC of pharmaceuticals is manual,requiring specially trained personnel,a range of expensive analytical and chemical equipment and laboratory space,the consumption of many samples,and usually a long time.Compared with ordinary pharmaceuticals,radiopharmaceuticals have the following unique characteristics:radioactivity,short lifetime,low synthesis yield,and high cost.Therefore,analytical methods and instrumentation must be exclusively developed for the QC of radiopharmaceuticals to avoid large losses owing to radioactive decay or handling.Microfluidics integrates microchannels or microchambers into several square centimeters of a microscale chip through micro-nanofabrication,allowing a precise manipulation of the fluid in microtubules,where various traditional physical,chemical,or biological experiments occur.Microfluidics is gaining attention in the field of analytical testing owing to significantly reduced consumption of samples and reagents,reduced analysis time,increased detection sensitivity,increased multiplexing,and reduced instrument size.Features such as micro size,micro volume,high sensitivity,and on-line testing have led to increasing interest in microfluidics.This review covers the development of integrated microfluidic QC devices that can automatically process,test,analyze,and calculate completed test metrics online.展开更多
A theoretical analysis regarding active vibration control of rotating machines with current-controlled electrodynamic actuators between machine feet and steel frame foundation and with velocity feedback of the machine...A theoretical analysis regarding active vibration control of rotating machines with current-controlled electrodynamic actuators between machine feet and steel frame foundation and with velocity feedback of the machine feet vibrations is presented.First,a generalized mathematical formulation is derived based on a state-space description which can be used for different kinds of models(1D,2D,and 3D models).It is shown that under special boundary conditions,the control parameters can be directly implemented into the stiffness and damping matrices of the system.Based on the generalized mathematical formulation,an example of a rotating machine—described by a 2D model—with journal bearings,flexible rotor,current-controlled electrodynamic actuators,steel frame foundation,and velocity feedback of the machine feet vibrations is presented where the effectiveness of the described active vibration control system is demonstrated.展开更多
Age-related macular degeneration(AMD)is a disease that affects the vision of elderly individuals worldwide.Although current therapeutics have shown effectiveness against AMD,some patients may remain unresponsive and c...Age-related macular degeneration(AMD)is a disease that affects the vision of elderly individuals worldwide.Although current therapeutics have shown effectiveness against AMD,some patients may remain unresponsive and continue to experience disease progression.Therefore,in-depth knowledge of the mechanism underlying AMD pathogenesis is urgently required to identify potential drug targets for AMD treatment.Recently,studies have suggested that dysfunction of mitochondria can lead to the aggregation of reactive oxygen species(ROS)and activation of the cyclic GMP-AMP synthase(cGAS)/stimulator of interferon genes(STING)innate immunity pathways,ultimately resulting in sterile inflammation and cell death in various cells,such as cardiomyocytes and macrophages.Therefore,combining strategies targeting mitochondrial dysfunction and inflammatory mediators may hold great potential in facilitating AMD management.Notably,emerging evidence indicates that natural products targeting mitochondrial quality control(MQC)and the cGAS/STING innate immunity pathways exhibit promise in treating AMD.Here,we summarize phytochemicals that could directly or indirectly influence the MQC and the cGAS/STING innate immunity pathways,as well as their interconnected mediators,which have the potential to mitigate oxidative stress and suppress excessive inflammatory responses,thereby hoping to offer new insights into therapeutic interventions for AMD treatment.展开更多
Crotalaria ferruginea Graham ex Benth.is a commonly used herb among ethnic minorities.Its whole plant is used as medicine for conditions such as heatstroke,tinnitus,hearing loss,phlegm heat cough,gum swelling and pain...Crotalaria ferruginea Graham ex Benth.is a commonly used herb among ethnic minorities.Its whole plant is used as medicine for conditions such as heatstroke,tinnitus,hearing loss,phlegm heat cough,gum swelling and pain,lower back and knee pain,vaginal discharge and infantile malnutrition.Modern pharmaceutical research has found that Crotalaria ferruginea Graham ex Benth.mainly contains flavonoids,steroids,organic acids and terpenes,which have antibacterial,free radical scavenging,antiinflammatory and other effects.Quality control mainly focuses on characteristics,identification,content determination,etc.This article summarizes the recent research progress on the chemical composition,pharmacological effects,quality control and extraction process of Crotalaria ferruginea Graham ex Benth.on the basis of existing Crotalaria ferruginea Graham ex Benth.research reports.展开更多
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pur...To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombinati...Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.展开更多
To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction...To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction-Order(FO)sliding-mode Fault-Tolerant Cooperative Control(FTCC)strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism(ET-COM-M)and Event-Triggered Control Mechanism(ET-CON-M).First,by considering the limited communication bandwidth of multiple UAVs in formation,an ET-COM-M is designed to significantly reduce communication times.Then,a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs.Moreover,the adaptive strategy is incorporated into the Radial Basis Function Neural Network(RBFNN)to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties.Besides,the Nussbaum method is used to deal with the loss-of-effectiveness faults.To further achieve the refined control performance against faults,FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M.Finally,Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy.Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism(ETM)can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies,making the developed control scheme applicable in engineering.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
文摘Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.
基金supported by National Key Research and Development Program of China(Grant No.2023YFB4604100)National Key Research and Development Program of China(Grant No.2022YFB3806104)+4 种基金Key Research and Development Program in Shaanxi Province(Grant No.2021LLRH-08-17)Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001)K C Wong Education Foundation of ChinaYouth Innovation Team of Shaanxi Universities of ChinaKey Research and Development Program of Shaanxi Province(Grant 2021LLRH-08-3.1).
文摘Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exacerbates this challenge by rendering the process vulnerable to environmental changes and unexpected factors,resulting in defects and inconsistent product quality,particularly in unmanned long-term operations or printing in extreme environments.To address these issues,we developed a process monitoring and closed-loop feedback control strategy for the 3D printing process.Real-time printing image data were captured and analyzed using a well-trained neural network model,and a real-time control module-enabled closed-loop feedback control of the flow rate was developed.The neural network model,which was based on image processing and artificial intelligence,enabled the recognition of flow rate values with an accuracy of 94.70%.The experimental results showed significant improvements in both the surface performance and mechanical properties of printed composites,with three to six times improvement in tensile strength and elastic modulus,demonstrating the effectiveness of the strategy.This study provides a generalized process monitoring and feedback control method for the 3D printing of continuous fiber-reinforced composites,and offers a potential solution for remote online monitoring and closed-loop adjustment in unmanned or extreme space environments.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2021B0301030001)the National Key Research and Development Program of China(Grant No.2021YFB3802300)the Foundation of National Key Laboratory of Shock Wave and Detonation Physics(Grant No.JCKYS2022212004)。
文摘The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
基金supported by the National Key R&D Program of China(No.2024YFB4609700)Major Research Plan of the National Natural Science Foundation of China(No.92266102)+4 种基金National Natural Science Foundation of China(No.52271135,No.52433016)Open project of Key Laboratory of Green Fabrication and Surface Technology of Advanced Metal Materials,China(No.GFST2024KF05)Innovative Research Group Project of Hubei Provincial Natural Science Foundation,China(No.2025AFA014)ECU DVC Strategic Research Support Fund,Australia(No.23965)Natural Science Foundation of Hubei Province,China(No.2025AFD399).
文摘Additive manufacturing(AM)promotes the production of metallic parts with significant design flexibility,yet its use in critical applications is hindered by challenges in ensuring consistent quality and performance.Process variability often leads to defects,insufficient geometric accuracy and inadequate material properties,which are difficult to effectively manage due to limitations of traditional quality control methods in modeling highdimensional nonlinear relationships and enabling adaptive control.Machine learning(ML)offers a transformative approach to model intricate process-structure-property relationships by leveraging the rich data environment of AM.The study presents a comprehensive examination of ML-driven quality assurance implementations in metallic AM.First,it uniquely examines the innovative exploration of ML in predicting and understanding the fundamental multi-physics fields that influence the quality of a fabricated component,including temperature fields,fluid dynamics and stress/strain evolution.Subsequently,the application of ML in optimizing key quality attributes,including defect detection and mitigation(porosity,cracks,etc.),geometric fidelity enhancement(dimensional accuracy,surface roughness,etc.)and material property tailoring(mechanical strength,fatigue life,corrosion resistance,etc.),are discussed in detail.Finally,the development of ML-driven real-time closed-loop control systems for intelligent quality assurance,the strategies for addressing the data scarcity and cross-scenario transferability in metal AM are discussed.This article provides a novel perspective on the profound potential of ML technology for metal AM quality control applications,highlights the challenges faced during research,and outlines future development directions.
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
文摘The high necessity to develop novel and optimized technologies for crop production is very high due to the exponential growth in term of world population of the last years.In this field a novel use of fertilizers and pesticides can ameliorate the life conditions around the world due to the higher productivity with lower losses and consequent less environmental problems related to pollution.To address these challenges a very promising solution is constituted by devices able to control and sustain the release of fertilizers and pesticide optimizing their efficacy preserving the environment.In the last decade a lot of efforts,in terms of research,were dedicated to the development of smart devices that can address those issues maintaining also low costs and easy production processes.In this review we will point the attention on devices that can be used as slow release systems for fertilizers and/or pesticides.In details strong consideration will be devoted to their formulation to increase the knowledge on the high number of possibilities behind these novel and smart devices.
基金National Natural ScienceFoundation of China (grant number: 81973696).
文摘Gualou-Xiebai-Banxia Decoction(GXBD)is a traditional Chinese herbal formula including four traditional Chinese medicines:Gualou(Trichosanthis Fructus,TF),Xiebai(Allii Macrostemonis Bulbus,AMB),Banxia(Pinelliae Rhizoma,PR)and yellow wine.It is a classical therapy for chest stuffiness and pain syndrome and is widely used in the clinical treatment of coronary heart disease.It also shows significant therapeutic effects on pulmonary heart disease,hyperlipidemia,and arrhythmia.This study conducted a literature review and collected information on GXBD from databases such as PubMed,Web of Science,China National Knowledge Infrastructure,and ScienceDirect.The result indicated that the main active ingredients of GXBD are steroids,flavonoids,terpenoids,alkaloids,amino acids,and organic acids.Trigonelline,macrostemonoside and cucurbitacin B can provide reference for its quality control.GXBD may exert therapeutic effects on coronary heart disease through AMPK,PI3K-AKT,oxLDL,VEGF,and NF-κB signal pathways.This review provides a comprehensive analysis and summary of the chemical composition and in vivo metabolism of three traditional Chinese medicines(TF,AMB,and PR),along with an evaluation of the chemical composition,quality control,pharmacological effects,and clinical application of GXBD.Based on these,areas requiring further research on GXBD have been proposed to provide a reference for its further development and new drug research.
基金supported by National Natural Science Foundation of China(Grants 32027802 and 22178307)National Key Research and Development Program of China(Grant 2021YFA1101700)the Science Technology Department of Zhejiang Province(Grant 2024C03100).
文摘Radionuclide imaging is divided into positron emission tomography and single photon emission tomography and is widely used in clinical practice for diagnosis and treatment,as well as in clinical research for the development and evaluation of new therapies.Although it is a visually intuitive form of three-dimensional functional imaging,this modality requires the injection of radiopharmaceuticals labeled with positron-or gamma-emitting isotopes into patients to assess and quantify anabolism,gene expression,and other processes.For this reason,radiopharmaceuticals must undergo rigorous quality control(QC)to ensure product purity,efficacy,and safety.Traditional QC of pharmaceuticals is manual,requiring specially trained personnel,a range of expensive analytical and chemical equipment and laboratory space,the consumption of many samples,and usually a long time.Compared with ordinary pharmaceuticals,radiopharmaceuticals have the following unique characteristics:radioactivity,short lifetime,low synthesis yield,and high cost.Therefore,analytical methods and instrumentation must be exclusively developed for the QC of radiopharmaceuticals to avoid large losses owing to radioactive decay or handling.Microfluidics integrates microchannels or microchambers into several square centimeters of a microscale chip through micro-nanofabrication,allowing a precise manipulation of the fluid in microtubules,where various traditional physical,chemical,or biological experiments occur.Microfluidics is gaining attention in the field of analytical testing owing to significantly reduced consumption of samples and reagents,reduced analysis time,increased detection sensitivity,increased multiplexing,and reduced instrument size.Features such as micro size,micro volume,high sensitivity,and on-line testing have led to increasing interest in microfluidics.This review covers the development of integrated microfluidic QC devices that can automatically process,test,analyze,and calculate completed test metrics online.
文摘A theoretical analysis regarding active vibration control of rotating machines with current-controlled electrodynamic actuators between machine feet and steel frame foundation and with velocity feedback of the machine feet vibrations is presented.First,a generalized mathematical formulation is derived based on a state-space description which can be used for different kinds of models(1D,2D,and 3D models).It is shown that under special boundary conditions,the control parameters can be directly implemented into the stiffness and damping matrices of the system.Based on the generalized mathematical formulation,an example of a rotating machine—described by a 2D model—with journal bearings,flexible rotor,current-controlled electrodynamic actuators,steel frame foundation,and velocity feedback of the machine feet vibrations is presented where the effectiveness of the described active vibration control system is demonstrated.
基金funded by Chinese NSFC(Grant Nos.:82373336,82303238,and U22A20311,Sichuan Science and Technology Department,China(GrantNos.:2024NSFSC1945,,and 2023NSFSC0667)the Third People's Hospital of Chengdu Clinical Research Program,China(Grant Nos.:CSY-YN-01-2023-013,CSYYN-01-2023-005,and CSY-YN-03-2024-003)+1 种基金Sichuan University“From O to 1”Innovative Research Project,China(Project No.:2023SCUH0024)Health Commission of Chengdu,China(Grant No.:2024291).
文摘Age-related macular degeneration(AMD)is a disease that affects the vision of elderly individuals worldwide.Although current therapeutics have shown effectiveness against AMD,some patients may remain unresponsive and continue to experience disease progression.Therefore,in-depth knowledge of the mechanism underlying AMD pathogenesis is urgently required to identify potential drug targets for AMD treatment.Recently,studies have suggested that dysfunction of mitochondria can lead to the aggregation of reactive oxygen species(ROS)and activation of the cyclic GMP-AMP synthase(cGAS)/stimulator of interferon genes(STING)innate immunity pathways,ultimately resulting in sterile inflammation and cell death in various cells,such as cardiomyocytes and macrophages.Therefore,combining strategies targeting mitochondrial dysfunction and inflammatory mediators may hold great potential in facilitating AMD management.Notably,emerging evidence indicates that natural products targeting mitochondrial quality control(MQC)and the cGAS/STING innate immunity pathways exhibit promise in treating AMD.Here,we summarize phytochemicals that could directly or indirectly influence the MQC and the cGAS/STING innate immunity pathways,as well as their interconnected mediators,which have the potential to mitigate oxidative stress and suppress excessive inflammatory responses,thereby hoping to offer new insights into therapeutic interventions for AMD treatment.
文摘Crotalaria ferruginea Graham ex Benth.is a commonly used herb among ethnic minorities.Its whole plant is used as medicine for conditions such as heatstroke,tinnitus,hearing loss,phlegm heat cough,gum swelling and pain,lower back and knee pain,vaginal discharge and infantile malnutrition.Modern pharmaceutical research has found that Crotalaria ferruginea Graham ex Benth.mainly contains flavonoids,steroids,organic acids and terpenes,which have antibacterial,free radical scavenging,antiinflammatory and other effects.Quality control mainly focuses on characteristics,identification,content determination,etc.This article summarizes the recent research progress on the chemical composition,pharmacological effects,quality control and extraction process of Crotalaria ferruginea Graham ex Benth.on the basis of existing Crotalaria ferruginea Graham ex Benth.research reports.
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
基金funded by the National Key Research and Development Program of China,grant number:2023YFF0615404.
文摘To overcome the challenges associated with predicting gas extraction performance and mitigating the gradual decline in extraction volume,which adversely impacts gas utilization efficiency in mines,a gas extraction pure volume prediction model was developed using Support Vector Regression(SVR)and Random Forest(RF),with hyperparameters fine-tuned via the Genetic Algorithm(GA).Building upon this,an adaptive control model for gas extraction negative pressure was formulated to maximize the extracted gas volume within the pipeline network,followed by field validation experiments.Experimental results indicate that the GA-SVR model surpasses comparable models in terms of mean absolute error,root mean square error,and mean absolute percentage error.In the extraction process of bedding boreholes,the influence of negative pressure on gas extraction concentration diminishes over time,yet it remains a critical factor in determining the extracted pure volume.In contrast,throughout the entire extraction period of cross-layer boreholes,both extracted pure volume and concentration exhibit pronounced sensitivity to fluctuations in extraction negative pressure.Field experiments demonstrated that the adaptive controlmodel enhanced the average extracted gas volume by 5.08% in the experimental borehole group compared to the control group during the later extraction stage,with a more pronounced increase of 7.15% in the first 15 days.The research findings offer essential technical support for the efficient utilization and long-term sustainable development of mine gas resources.The research findings offer essential technical support for gas disaster mitigation and the sustained,efficient utilization of mine gas.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金Supported by National Natural Science Foundation of China(Grant Nos.52005039,51575043,51975048,U1764257).
文摘Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.
基金supported in part by National Natural Science Foundation of China(Nos.62373188,62003162)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20240182,BK20222012)+2 种基金the Industry-University Research Innovation Foundation for the Chinese Ministry of Education(No.2021ZYA02005)the Aeronautical Science Foundation of China(Nos.20220007052003,20200007018001)the Fundamental Research Funds for the Central Universities,China(Nos.NE2024004,NI2024001)。
文摘To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction-Order(FO)sliding-mode Fault-Tolerant Cooperative Control(FTCC)strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism(ET-COM-M)and Event-Triggered Control Mechanism(ET-CON-M).First,by considering the limited communication bandwidth of multiple UAVs in formation,an ET-COM-M is designed to significantly reduce communication times.Then,a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs.Moreover,the adaptive strategy is incorporated into the Radial Basis Function Neural Network(RBFNN)to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties.Besides,the Nussbaum method is used to deal with the loss-of-effectiveness faults.To further achieve the refined control performance against faults,FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M.Finally,Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy.Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism(ETM)can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies,making the developed control scheme applicable in engineering.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
