This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mod...This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.展开更多
Panoramic images, offering a 360-degree view, are essential in virtual reality(VR) and augmented reality(AR), enhancing realism with high-quality textures. However, acquiring complete and high-quality panoramic textur...Panoramic images, offering a 360-degree view, are essential in virtual reality(VR) and augmented reality(AR), enhancing realism with high-quality textures. However, acquiring complete and high-quality panoramic textures is challenging. This paper introduces a method using generative adversarial networks(GANs) and the contrastive language-image pretraining(CLIP) model to restore and control texture in panoramic images. The GAN model captures complex structures and maintains consistency, while CLIP enables fine-grained texture control via semantic text-image associations. GAN inversion optimizes latent codes for precise texture details. The resulting low dynamic range(LDR) images are converted to high dynamic range(HDR) using the Blender engine for seamless texture blending. Experimental results demonstrate the effectiveness and flexibility of this method in panoramic texture restoration and generation.展开更多
In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This me...In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.展开更多
With the expansion of the Internet market,the traditional software development method has been difficult to meet the market demand due to the problems of long development cycle,tedious work,and difficult system mainte...With the expansion of the Internet market,the traditional software development method has been difficult to meet the market demand due to the problems of long development cycle,tedious work,and difficult system maintenance.Therefore,to improve software development efficiency,this study uses residual networks and bidirectional long short-term memory(BLSTM)networks to improve the Pix2code model.The experiment results show that after improving the visual module of the Pix2code model using residual networks,the accuracy of the training set improves from 0.92 to 0.96,and the convergence time is shortened from 3 hours to 2 hours.After using a BLSTM network to improve the language module and decoding layer,the accuracy and convergence speed of the model have also been improved.The accuracy of the training set grew from 0.88 to 0.92,and the convergence time was shortened by 0.5 hours.However,models improved by BLSTM networks might exhibit overfitting,and thus this study uses Dropout and Xavier normal distribution to improve the memory network.The results validate that the training set accuracy of the optimized BLSTM network remains around 0.92,but the accuracy of the test set has improved to a maximum of 85%.Dropout and Xavier normal distributions can effectively improve the overfitting problem of BLSTM networks.Although they can also decrease the model’s stability,their gain is higher.The training and testing accuracy of the Pix2code improved by residual network and BLSTM network are 0.95 and 0.82,respectively,while the code generation accuracy of the original Pix2code is only 0.77.The above data indicate that the improved Pix2code model has improved the accuracy and stability of code automatic generation.展开更多
With the development of computer technology, embedded control system plays an important role in modern industry. For the embedded system, traditional development methods are time-consuming and system is not easy to ma...With the development of computer technology, embedded control system plays an important role in modern industry. For the embedded system, traditional development methods are time-consuming and system is not easy to maintain. Domain-specific modeling provides a solution for the problems. In this paper, we proposed development architecture for embedded control systems based on MIC. GME is used to construct meta-model and application model, model in-terpreter interprets model and stores model information in xml format document. The final cross-platform codes are automatically generated by different templates and xml format document. This development method can reduce time and cost in the lifecycle of system development.展开更多
Peeling trunk,binding insect-attracting belt,cleaning orchard and soil-covering under the crown were the control methods on overwintering generation of oriental fruit moth.However,they had not been applied widely on t...Peeling trunk,binding insect-attracting belt,cleaning orchard and soil-covering under the crown were the control methods on overwintering generation of oriental fruit moth.However,they had not been applied widely on the production because of the lack of systematic quantitative evaluation.Aiming at this fact,the control effects of these technical measures were studied in peach with different ripening period.The results showed that peeling trunk was the best with the control effect of88.64%.The control effect of binding insect-attracting belt of grass bundle was74.13%,which was the most economical and efficient.Covering with soil layer of 3cm under the crown during the middle ten days of March could holdback the adult getting out from soil.Cleaning deadwood could clean out the overwintering larvae on the ground.展开更多
Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable...Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.展开更多
Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system ...Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.展开更多
Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing...Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.展开更多
A path following control algorithm for an unmanned underwater vehicle（UUV） using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and or...A path following control algorithm for an unmanned underwater vehicle（UUV） using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and orientation,the path following control in the horizontal plane may yield a poor performance.To deal with the negative effect induced by initial states,a temporary path generation was presented based on the relationship between the original reference path and the vehicle’s initial states.With different relative positions between the vehicle and reference path,including out of straight lines,as well as inside and outside a circle,the related temporary paths guiding the vehicle to the reference path were able to be generated in real time.The vehicle was guided to steer along the temporary path until it reached the tangent point at the reference path,where the controller was designed using the input-output feedback linearization method.Simulation results demonstrated that the proposed algorithm is effective under the three different situations mentioned above.展开更多
We propose and experimentally demonstrate an integrated silicon photonic scheme to generate multi-channel millimeter-wave(MMW) signals for 5 G multi-user applications. The fabricated silicon photonic chip has a footpr...We propose and experimentally demonstrate an integrated silicon photonic scheme to generate multi-channel millimeter-wave(MMW) signals for 5 G multi-user applications. The fabricated silicon photonic chip has a footprint of 1.1 × 2.1 mm^2 and integrates 7 independent channels each having on-chip polarization control and heterodyne mixing functions. 7 channels of4-Gb/s QPSK baseband signals are delivered via a 2-km multi-core fiber(MCF) and coupled into the chip with a local oscillator(LO) light. The polarization state of each signal light is automatically adjusted and aligned with that of the LO light, and then 7 channels of 28-GHz MMW carrying 4-Gb/s QPSK signals are generated by optical heterodyne beating. Automated polarizationcontrol function of each channel is also demonstrated with ～7-ms tuning time and ～27-dB extinction ratio.展开更多
The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment suc...The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.展开更多
There are two prominent features in the process of temperature control in solar collector field.Firstly,the dynamic model of solar collector field is nonlinear and complex,which needs to be simplified.Secondly,there a...There are two prominent features in the process of temperature control in solar collector field.Firstly,the dynamic model of solar collector field is nonlinear and complex,which needs to be simplified.Secondly,there are a lot of random and uncontrollable,measurable and unmeasurable disturbances in solar collector field.This paper uses Taylor formula and difference approximation method to design a dynamic matrix predictive control(DMC)by linearizing and discretizing the dynamic model of the solar collector field.In addition,the purpose of controlling the stability of the outlet solar field salt temperature is achieved by adjusting the mass flow of molten salt.In order to further improve the ability of the system to suppress unmeasured disturbances,a steady-state Kalman filter is designed to estimate state variables,so that the system has better stability and robustness.The simulation verification results show that the DMC control system based on Kamlan filtering has better control effect than the traditional DMC control system.In the case of large fluctuations in solar radiation intensity and consideration of undetectable interference,the overshoot of the system is reduced by 4%and the rise time remains unchanged.展开更多
In the context of rising global energy demand and increasing awareness of environmental protection,photovoltaic power generation,as a clean and renewable form of energy,has become increasingly important and has receiv...In the context of rising global energy demand and increasing awareness of environmental protection,photovoltaic power generation,as a clean and renewable form of energy,has become increasingly important and has received widespread attention and application worldwide.However,during the construction and operation of mountain photovoltaic power generation projects,water and soil erosion has become a major challenge,which not only restricts the sustainable development process of the project,but also has a significant negative impact on the local ecological environment.This article deeply analyzes the multiple causes,extensive impacts and effective prevention and control strategies of water and soil erosion in mountain photovoltaic power generation projects.The results show that rainfall intensity,terrain slope,soil type and vegetation coverage are the four key factors leading to soil erosion.Soil erosion not only causes a sharp decline in soil fertility,but also aggravates the problem of sediment deposition in rivers and reservoirs,and poses a direct threat to the stability and operating efficiency of photovoltaic equipment.In order to deal with the above problems,this paper innovatively puts forward a series of soil and water conservation technologies,covering multiple dimensions such as engineering measures,plant measures,farming measures and temporary measures,and deeply discusses the application models and management strategies of these measures in key stages such as planning and design,construction,operation and maintenance.Through specific case analysis,the successful practical experience of soil and water conservation is refined and summarized,and the key role of community cooperation,technical support and modern monitoring technology in preventing and controlling soil and water erosion is further emphasized.This article aims to achieve a win-win situation of ecological environment protection and energy development and utilization through scientific planning and effective governance,and contribute to the construction of a green,low-carbon,and sustainable energy system.展开更多
For the characteristics of wind power generation system is multivariable, nonlinear and random, in this paper the neural network PID adaptive control is adopted. The size of pitch angle is adjusted in time to improve ...For the characteristics of wind power generation system is multivariable, nonlinear and random, in this paper the neural network PID adaptive control is adopted. The size of pitch angle is adjusted in time to improve the perfomance of power control. The PID parameters are corrected by the gradient descent method, and Radial Basis Functiion （RBF） neural network is used as the system identifier in this method. Sinlation results show that by using neural network adaptive PID controller the generator power control can inhibit effectively the speed and affect the output prover of generator. The dynamic performnce and robustness of the controlled system is good, and the peformance of wind power system is improved.展开更多
A trajectory generation method which is based on NURBS interpolation is studied to improve the fitting accuracy and smoothness of non-circular cross section and obtain higher accuracy of the final non-circular profile...A trajectory generation method which is based on NURBS interpolation is studied to improve the fitting accuracy and smoothness of non-circular cross section and obtain higher accuracy of the final non-circular profile control. After using the NURBS, the most optimized and smooth trajectory for the linear actuator can be obtained. For the purpose of machining the non-circular cross section by CNC turning, the fast response linear actuator has been used. The control algorithm which is compound control of proportional-integral-differential （PID） and iterative learning control has been developed for non-circular profile generation. By using the NURBS interpolation and the compound control of PID and iterative learning control, the final motion accuracy of linear actuator has been improved, therefore, the machining accuracy of the non-circular turning can be improved.展开更多
For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection int...For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection interval control that operates at specified intervals and monitors the maximum power point. The author has obtained satisfactory results using this new MPPT control method. This paper investigates the application of the new MPPT control method for a PCS （power conditioning system） in a grid-connected type PV power generation system. The experimental results clearly demonstrate that the developed PCS offers outstanding effectiveness in tracking the maximum power point in partially shaded environments.展开更多
Structured flowchart( SFC) and Automatic code generation based on SFC( CG-SFC) have been widely used in software requirements,design and testing phases. Some CG-SFC tools such as Rhapsody have the ability to build flo...Structured flowchart( SFC) and Automatic code generation based on SFC( CG-SFC) have been widely used in software requirements,design and testing phases. Some CG-SFC tools such as Rhapsody have the ability to build flowchart and generate code,but they do not check whether a given flowchart is correct or structural. For unstructured error ‘goto'statements will be generated randomly. We proposed three algorithms and some error recognition criteria to solve those problems. Structure recognition algorithm can recognize Selection,While/for and do-while structures. Error recognition algorithm incorporating criteria can check all the errors. At last,we develop a CG-SFC system,and compared with existing Rhapsody,it shows that the proposed algorithms are correct and effective.展开更多
A hybrid Stochastic Fractal Search plus Pattern Search （hSFS-PS） based cascade PI-PD controller is suggested in this paper for Automatic Generation Control （AGC） of thermal, hydro and gas power unit based power sy...A hybrid Stochastic Fractal Search plus Pattern Search （hSFS-PS） based cascade PI-PD controller is suggested in this paper for Automatic Generation Control （AGC） of thermal, hydro and gas power unit based power systems in presence of Plug in Electric Vehicles （PEV）. Firstly, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral （I） controller is optimized by Stochastic FractaI Search （SFS） algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, differential evolution and teaching learning based optimization techniques is demonstrated by comparing simulation results for the identical power system. To improve the system performance further, Pattern Search （PS） is subsequently employed. The study is further extended for different controllers like PI, PID, and cascaded PI-PD controller and the superiority of cascade PI-PD controller over conventional controllers is demonstrated. Then, cascade PI- PD controller parameters of AGC searched using the proposed hSFS-PS algorithm in presence of plug in electric vehicles. The study is also extended to an interconnected power system. It is seen from the comparative analysis that hSFS-PS tuned PI-PD controller in single and multi-area with multi sources improves the system frequency stability in complicated situations. Lastly, a three area interconnected system with PEVs with dissimilar cascade PI-PD controller in each area is considered and proposed hSFS- PS algorithm is used to tune the controller parameters in presence of nonlinearities like rate constraint of units, dead zone of governor and communication delay.展开更多
Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recen...Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to.However,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in concealment.In this paper,we propose a topic-controlled steganography method which is guided by graph-to-text generation.The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation.Different from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional probability.We test our method in different aspects and compare it with other text generative steganographic methods.The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.展开更多
基金supported by the 2022 Sanya Science and Technology Innovation Project,China(No.2022KJCX03)the Sanya Science and Education Innovation Park,Wuhan University of Technology,China(Grant No.2022KF0028)the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City,China(Grant No.2021JJLH0036).
文摘This study investigates the Maximum Power Point Tracking(MPPT)control method of offshore windphotovoltaic hybrid power generation system with offshore crane-assisted.A new algorithm of Global Fast Integral Sliding Mode Control(GFISMC)is proposed based on the tip speed ratio method and sliding mode control.The algorithm uses fast integral sliding mode surface and fuzzy fast switching control items to ensure that the offshore wind power generation system can track the maximum power point quickly and with low jitter.An offshore wind power generation system model is presented to verify the algorithm effect.An offshore off-grid wind-solar hybrid power generation systemis built in MATLAB/Simulink.Compared with other MPPT algorithms,this study has specific quantitative improvements in terms of convergence speed,tracking accuracy or computational efficiency.Finally,the improved algorithm is further analyzed and carried out by using Yuankuan Energy’s ModelingTech semi-physical simulation platform.The results verify the feasibility and effectiveness of the improved algorithm in the offshore wind-solar hybrid power generation system.
文摘Panoramic images, offering a 360-degree view, are essential in virtual reality(VR) and augmented reality(AR), enhancing realism with high-quality textures. However, acquiring complete and high-quality panoramic textures is challenging. This paper introduces a method using generative adversarial networks(GANs) and the contrastive language-image pretraining(CLIP) model to restore and control texture in panoramic images. The GAN model captures complex structures and maintains consistency, while CLIP enables fine-grained texture control via semantic text-image associations. GAN inversion optimizes latent codes for precise texture details. The resulting low dynamic range(LDR) images are converted to high dynamic range(HDR) using the Blender engine for seamless texture blending. Experimental results demonstrate the effectiveness and flexibility of this method in panoramic texture restoration and generation.
基金supported by the National Natural Science Foundation of China Project(No.62302540),please visit their website at https://www.nsfc.gov.cn/(accessed on 18 June 2024)The Open Foundation of Henan Key Laboratory of Cyberspace Situation Awareness(No.HNTS2022020),Further details can be found at http://xt.hnkjt.gov.cn/data/pingtai/(accessed on 18 June 2024)Natural Science Foundation of Henan Province Youth Science Fund Project(No.232300420422),you can visit https://kjt.henan.gov.cn/2022/09-02/2599082.html(accessed on 18 June 2024).
文摘In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.
基金supported by National Natural Science Foundation of China(No.62062063)the Science and Technology Research Project of Jiangxi Provincial Department of Education,China(No.GJJ202310)the Jiangxi Provincial Natural Science Foundation,China(No.20224BAB202022).
文摘With the expansion of the Internet market,the traditional software development method has been difficult to meet the market demand due to the problems of long development cycle,tedious work,and difficult system maintenance.Therefore,to improve software development efficiency,this study uses residual networks and bidirectional long short-term memory(BLSTM)networks to improve the Pix2code model.The experiment results show that after improving the visual module of the Pix2code model using residual networks,the accuracy of the training set improves from 0.92 to 0.96,and the convergence time is shortened from 3 hours to 2 hours.After using a BLSTM network to improve the language module and decoding layer,the accuracy and convergence speed of the model have also been improved.The accuracy of the training set grew from 0.88 to 0.92,and the convergence time was shortened by 0.5 hours.However,models improved by BLSTM networks might exhibit overfitting,and thus this study uses Dropout and Xavier normal distribution to improve the memory network.The results validate that the training set accuracy of the optimized BLSTM network remains around 0.92,but the accuracy of the test set has improved to a maximum of 85%.Dropout and Xavier normal distributions can effectively improve the overfitting problem of BLSTM networks.Although they can also decrease the model’s stability,their gain is higher.The training and testing accuracy of the Pix2code improved by residual network and BLSTM network are 0.95 and 0.82,respectively,while the code generation accuracy of the original Pix2code is only 0.77.The above data indicate that the improved Pix2code model has improved the accuracy and stability of code automatic generation.
文摘With the development of computer technology, embedded control system plays an important role in modern industry. For the embedded system, traditional development methods are time-consuming and system is not easy to maintain. Domain-specific modeling provides a solution for the problems. In this paper, we proposed development architecture for embedded control systems based on MIC. GME is used to construct meta-model and application model, model in-terpreter interprets model and stores model information in xml format document. The final cross-platform codes are automatically generated by different templates and xml format document. This development method can reduce time and cost in the lifecycle of system development.
文摘Peeling trunk,binding insect-attracting belt,cleaning orchard and soil-covering under the crown were the control methods on overwintering generation of oriental fruit moth.However,they had not been applied widely on the production because of the lack of systematic quantitative evaluation.Aiming at this fact,the control effects of these technical measures were studied in peach with different ripening period.The results showed that peeling trunk was the best with the control effect of88.64%.The control effect of binding insect-attracting belt of grass bundle was74.13%,which was the most economical and efficient.Covering with soil layer of 3cm under the crown during the middle ten days of March could holdback the adult getting out from soil.Cleaning deadwood could clean out the overwintering larvae on the ground.
文摘Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.
文摘Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.
文摘Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.
基金Supported by the National Natural Science Foundation of China under Grant No.51179038the Program of New Century Excellent Talents in University under Grant No. NCET-10-0053
文摘A path following control algorithm for an unmanned underwater vehicle（UUV） using temporary path generation guidance was proposed in this paper.Owing to different initial states of the vehicle,such as position and orientation,the path following control in the horizontal plane may yield a poor performance.To deal with the negative effect induced by initial states,a temporary path generation was presented based on the relationship between the original reference path and the vehicle’s initial states.With different relative positions between the vehicle and reference path,including out of straight lines,as well as inside and outside a circle,the related temporary paths guiding the vehicle to the reference path were able to be generated in real time.The vehicle was guided to steer along the temporary path until it reached the tangent point at the reference path,where the controller was designed using the input-output feedback linearization method.Simulation results demonstrated that the proposed algorithm is effective under the three different situations mentioned above.
基金supported by the National Key R&D Pro-gram of China under Grant 2016YFB0402501in part by the Natural Science Foundation of China under grant 61605112Open Fund of IPOC under grant BUPT
文摘We propose and experimentally demonstrate an integrated silicon photonic scheme to generate multi-channel millimeter-wave(MMW) signals for 5 G multi-user applications. The fabricated silicon photonic chip has a footprint of 1.1 × 2.1 mm^2 and integrates 7 independent channels each having on-chip polarization control and heterodyne mixing functions. 7 channels of4-Gb/s QPSK baseband signals are delivered via a 2-km multi-core fiber(MCF) and coupled into the chip with a local oscillator(LO) light. The polarization state of each signal light is automatically adjusted and aligned with that of the LO light, and then 7 channels of 28-GHz MMW carrying 4-Gb/s QPSK signals are generated by optical heterodyne beating. Automated polarizationcontrol function of each channel is also demonstrated with ～7-ms tuning time and ～27-dB extinction ratio.
基金supported by Theoretical study of power system synergistic dispatch National Science Foundation of China(51477091).
文摘The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.
基金supported by the National Natural Science Foundation of China(Grant No.51667013)the Science and Technology Project of State Grid Corporation of China(Grant No.52272219000V).
文摘There are two prominent features in the process of temperature control in solar collector field.Firstly,the dynamic model of solar collector field is nonlinear and complex,which needs to be simplified.Secondly,there are a lot of random and uncontrollable,measurable and unmeasurable disturbances in solar collector field.This paper uses Taylor formula and difference approximation method to design a dynamic matrix predictive control(DMC)by linearizing and discretizing the dynamic model of the solar collector field.In addition,the purpose of controlling the stability of the outlet solar field salt temperature is achieved by adjusting the mass flow of molten salt.In order to further improve the ability of the system to suppress unmeasured disturbances,a steady-state Kalman filter is designed to estimate state variables,so that the system has better stability and robustness.The simulation verification results show that the DMC control system based on Kamlan filtering has better control effect than the traditional DMC control system.In the case of large fluctuations in solar radiation intensity and consideration of undetectable interference,the overshoot of the system is reduced by 4%and the rise time remains unchanged.
文摘In the context of rising global energy demand and increasing awareness of environmental protection,photovoltaic power generation,as a clean and renewable form of energy,has become increasingly important and has received widespread attention and application worldwide.However,during the construction and operation of mountain photovoltaic power generation projects,water and soil erosion has become a major challenge,which not only restricts the sustainable development process of the project,but also has a significant negative impact on the local ecological environment.This article deeply analyzes the multiple causes,extensive impacts and effective prevention and control strategies of water and soil erosion in mountain photovoltaic power generation projects.The results show that rainfall intensity,terrain slope,soil type and vegetation coverage are the four key factors leading to soil erosion.Soil erosion not only causes a sharp decline in soil fertility,but also aggravates the problem of sediment deposition in rivers and reservoirs,and poses a direct threat to the stability and operating efficiency of photovoltaic equipment.In order to deal with the above problems,this paper innovatively puts forward a series of soil and water conservation technologies,covering multiple dimensions such as engineering measures,plant measures,farming measures and temporary measures,and deeply discusses the application models and management strategies of these measures in key stages such as planning and design,construction,operation and maintenance.Through specific case analysis,the successful practical experience of soil and water conservation is refined and summarized,and the key role of community cooperation,technical support and modern monitoring technology in preventing and controlling soil and water erosion is further emphasized.This article aims to achieve a win-win situation of ecological environment protection and energy development and utilization through scientific planning and effective governance,and contribute to the construction of a green,low-carbon,and sustainable energy system.
基金supported by the Science and Technology Major Special Projects Gansu(No.0801GKDA058)
文摘For the characteristics of wind power generation system is multivariable, nonlinear and random, in this paper the neural network PID adaptive control is adopted. The size of pitch angle is adjusted in time to improve the perfomance of power control. The PID parameters are corrected by the gradient descent method, and Radial Basis Functiion （RBF） neural network is used as the system identifier in this method. Sinlation results show that by using neural network adaptive PID controller the generator power control can inhibit effectively the speed and affect the output prover of generator. The dynamic performnce and robustness of the controlled system is good, and the peformance of wind power system is improved.
基金the Tenth Five-Year National Science and Technology Key Project of China(No.BA203B04).
文摘A trajectory generation method which is based on NURBS interpolation is studied to improve the fitting accuracy and smoothness of non-circular cross section and obtain higher accuracy of the final non-circular profile control. After using the NURBS, the most optimized and smooth trajectory for the linear actuator can be obtained. For the purpose of machining the non-circular cross section by CNC turning, the fast response linear actuator has been used. The control algorithm which is compound control of proportional-integral-differential （PID） and iterative learning control has been developed for non-circular profile generation. By using the NURBS interpolation and the compound control of PID and iterative learning control, the final motion accuracy of linear actuator has been improved, therefore, the machining accuracy of the non-circular turning can be improved.
文摘For a standalone PV （photovoltaic） power generation system, the author previously proposed a new MPPT （maximum power point tracking） control method in which the I-V characteristics are scanned with a detection interval control that operates at specified intervals and monitors the maximum power point. The author has obtained satisfactory results using this new MPPT control method. This paper investigates the application of the new MPPT control method for a PCS （power conditioning system） in a grid-connected type PV power generation system. The experimental results clearly demonstrate that the developed PCS offers outstanding effectiveness in tracking the maximum power point in partially shaded environments.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61402131)the China Postdoctoral Science Foundation(Grant No.2014M551245,2016T90293)+1 种基金the Heilongjiang Postdoctoral Science Foundation(Grant No.LBH-Z13105)the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201651)
文摘Structured flowchart( SFC) and Automatic code generation based on SFC( CG-SFC) have been widely used in software requirements,design and testing phases. Some CG-SFC tools such as Rhapsody have the ability to build flowchart and generate code,but they do not check whether a given flowchart is correct or structural. For unstructured error ‘goto'statements will be generated randomly. We proposed three algorithms and some error recognition criteria to solve those problems. Structure recognition algorithm can recognize Selection,While/for and do-while structures. Error recognition algorithm incorporating criteria can check all the errors. At last,we develop a CG-SFC system,and compared with existing Rhapsody,it shows that the proposed algorithms are correct and effective.
文摘A hybrid Stochastic Fractal Search plus Pattern Search （hSFS-PS） based cascade PI-PD controller is suggested in this paper for Automatic Generation Control （AGC） of thermal, hydro and gas power unit based power systems in presence of Plug in Electric Vehicles （PEV）. Firstly, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral （I） controller is optimized by Stochastic FractaI Search （SFS） algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, differential evolution and teaching learning based optimization techniques is demonstrated by comparing simulation results for the identical power system. To improve the system performance further, Pattern Search （PS） is subsequently employed. The study is further extended for different controllers like PI, PID, and cascaded PI-PD controller and the superiority of cascade PI-PD controller over conventional controllers is demonstrated. Then, cascade PI- PD controller parameters of AGC searched using the proposed hSFS-PS algorithm in presence of plug in electric vehicles. The study is also extended to an interconnected power system. It is seen from the comparative analysis that hSFS-PS tuned PI-PD controller in single and multi-area with multi sources improves the system frequency stability in complicated situations. Lastly, a three area interconnected system with PEVs with dissimilar cascade PI-PD controller in each area is considered and proposed hSFS- PS algorithm is used to tune the controller parameters in presence of nonlinearities like rate constraint of units, dead zone of governor and communication delay.
基金supported in part by the National Natural Science Foundation of China [62102136]the 2020 Opening Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering [2020SDSJ06]the Construction Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering [2019ZYYD007].
文摘Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to.However,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in concealment.In this paper,we propose a topic-controlled steganography method which is guided by graph-to-text generation.The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation.Different from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional probability.We test our method in different aspects and compare it with other text generative steganographic methods.The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.
