The information exchange among satellites is crucial for the implementation of cluster satellite cooperative missions.However,achieving fast perception,rapid networking,and highprecision time synchronization among nod...The information exchange among satellites is crucial for the implementation of cluster satellite cooperative missions.However,achieving fast perception,rapid networking,and highprecision time synchronization among nodes without the support of the Global Navigation Satellite System(GNSS)and other prior information remains a formidable challenge to real-time wireless networks design.Therefore,a self-organizing network methodology based on multi-agent negotiation is proposed,which autonomously determines the master node through collaborative negotiation and competitive elections.On this basis,a real-time network protocol design is carried out and a high-precision time synchronization method with motion compensation is proposed.Simulation results demonstrate that the proposed method enables rapid networking with the capability of selfdiscovery,self-organization,and self-healing.For a cluster of 8 satellites,the networking time and the reorganization time are less than 4 s.The time synchronization accuracy exceeds 10-10s with motion compensation,demonstrating excellent real-time performance and stability.The research presented in this paper provides a valuable reference for the design and application of spacebased self-organizing networks for satellite cluster.展开更多
With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FD...With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FDN),the calculation of carbon flow distribution in FDN is more difficult.To this end,this study constructs a model for low-carbon optimal operations within the FDN on the basis of enhanced carbon emission flow(CEF).First,the carbon emission characteristics of FDNs are scrutinized and an improved method for calculating carbon flow within these networks is proposed.Subsequently,a model for optimizing low-carbon operations within FDNs is formulated based on the refined CEF,which merges the specificities of DG and intelligent SOP.Finally,this model is scrutinized using an upgraded IEEE 33-node distribution system,a comparative analysis of the cases reveals that when DG and SOP are operated in a coordinated manner in the FDN,with the cost of electricity generation was reduced by 40.63 percent and the cost of carbon emissions by 10.18 percent.The findings indicate that the judicious optimization of areas exhibiting higher carbon flow rates can effectively enhance the economic efficiency of DN operations and curtail the carbon emissions of the overall network.展开更多
Dealing with uncertainty is one of practical issues in design and operation of heat exchanger networks(HENs),arising the problem of flexible HEN synthesis.This paper addresses the state-of-the-art methods for flexible...Dealing with uncertainty is one of practical issues in design and operation of heat exchanger networks(HENs),arising the problem of flexible HEN synthesis.This paper addresses the state-of-the-art methods for flexible HEN synthesis based on sensitivity analysis,resilience analysis,flexibility analysis and multiperiod synthesis techniques as well.Each of these methods is summarized by presenting their general procedures and recent developments on modeling,solving strategies and applications.Some current topics related to flexible process synthesis have been briefly presented to provide several future research possibilities.展开更多
This paper mainly focuses on designing a sliding mode boundary controller for a single flexible-link manipulator based on adaptive radial basis function （RBF） neural network. The flexible manipulator in this paper i...This paper mainly focuses on designing a sliding mode boundary controller for a single flexible-link manipulator based on adaptive radial basis function （RBF） neural network. The flexible manipulator in this paper is considered to be an Euler-Bernoulli beam. We first obtain a partial differential equation （PDE） model of single-link flexible manipulator by using Hamiltons approach. To improve the control robustness, the system uncertainties including modeling uncertainties and external disturbances are compensated by an adaptive neural approximator. Then, a sliding mode control method is designed to drive the joint to a desired position and rapidly suppress vibration on the beam. The stability of the closed-loop system is validated by using Lyapunov＇s method based on infinite dimensional model, avoiding problems such as control spillovers caused by traditional finite dimensional truncated models. This novel controller only requires measuring the boundary information, which facilitates implementation in engineering practice. Favorable performance of the closed-loop system is demonstrated by numerical simulations.展开更多
This paper aims at modeling and developing vibration control methods for a flexible piezoelectric beam. A collocated sensor/actuator placement is used. Finite element analysis （FEA） method is adopted to derive the d...This paper aims at modeling and developing vibration control methods for a flexible piezoelectric beam. A collocated sensor/actuator placement is used. Finite element analysis （FEA） method is adopted to derive the dynamics model of the system. A back propagation neural network （BPNN） based proportional-derivative （PD） algorithm is applied to suppress the vibration. Simulation and experiments are conducted using the FEA model and BPNN-PD control law. Experimental results show good agreement with the simulation results using finite element modeling and the neural network control algorithm.展开更多
A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network(HEN)by genetic/simulated annealing algorithms(GA/SA).Through taking into account the ef...A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network(HEN)by genetic/simulated annealing algorithms(GA/SA).Through taking into account the effect of fouling process on optimal network topology,a preliminary network structure possessing two-fold oversynthesis is obtained by means of pseudo-temperature enthalpy(T-H)diagram approach prior to simultaneous optimization.Thus,the computational complexity of this problem classified as NP(Non-deterministic Polynomial)-complete can be significantly reduced.The promising matches resulting from preliminary synthesis stage are further optimized in parallel with their heat exchange areas and cleaning schedule.In addition,a novel continu- ous time representation is introduced to subdivide the given time horizon into several variable-size intervals according to operating periods of heat exchangers,and then flexible HEN synthesis can be implemented in dynamic manner.A numerical example is provided to demonstrate that the presented strategy is feasible to decrease the total annual cost(TAC)and further improve network flexibility,but even more important,it may be applied to solve large-scale flexible HEN synthesis problems.展开更多
The length of fexible manipulators with a telescopic arm alters during movement.The dynamic parameters of telescopic fexible manipulators exhibit signifcant time-varying characteristics owing to variations in length.W...The length of fexible manipulators with a telescopic arm alters during movement.The dynamic parameters of telescopic fexible manipulators exhibit signifcant time-varying characteristics owing to variations in length.With an increase in the manipulators’length,the nonlinear terms caused by fexibility in the manipulators’dynamic equations cannot be ignored.The time-varying characteristics and nonlinear terms of telescopic fexible manipulators cause fuctuations in rotation angles,which afect the operation accuracy of end-efectors.In this study,a control strategy based on a combination of fuzzy adjustment and an RBF neural network is utilized to improve the control accuracy of fexible telescopic manipulators.First,the dynamic equation of the manipulators is established using the assumed mode method and Lagrange’s principle,and the infuence of nonlinear terms is analyzed.Subsequently,a combined control strategy is proposed to suppress the fuctuation of the rotation angle in telescopic fexible manipulators.The variation ranges of the feedforward PD controller parameters are determined by the pole placement strategy and length of the manipulators.Fuzzy rules are utilized to adjust the controller parameters in real-time.The RBF neural network is utilized to identify and compensate the uncertain part of the dynamic model of the fexible manipulators.The uncertain part comprises time-varying parameters and nonlinear terms.Finally,numerical simulations and prototype experiments prove the efectiveness of the combined control strategy.The results prove that the proposed control strategy has a smaller standard deviation of errors.Therefore,the combined control strategy is more suitable for telescopic fexible manipulators,which can efectively improve the control accuracy of rotation angles.展开更多
Due to the widespread use of the Internet,customer information is vulnerable to computer systems attack,which brings urgent need for the intrusion detection technology.Recently,network intrusion detection has been one...Due to the widespread use of the Internet,customer information is vulnerable to computer systems attack,which brings urgent need for the intrusion detection technology.Recently,network intrusion detection has been one of the most important technologies in network security detection.The accuracy of network intrusion detection has reached higher accuracy so far.However,these methods have very low efficiency in network intrusion detection,even the most popular SOM neural network method.In this paper,an efficient and fast network intrusion detection method was proposed.Firstly,the fundamental of the two different methods are introduced respectively.Then,the selforganizing feature map neural network based on K-means clustering(KSOM)algorithms was presented to improve the efficiency of network intrusion detection.Finally,the NSLKDD is used as network intrusion data set to demonstrate that the KSOM method can significantly reduce the number of clustering iteration than SOM method without substantially affecting the clustering results and the accuracy is much higher than Kmeans method.The Experimental results show that our method can relatively improve the accuracy of network intrusion and significantly reduce the number of clustering iteration.展开更多
Highly conductive polymer composites(CPCs) with excellent mechanical flexibility are ideal materials for designing excellent electromagnetic interference(EMI) shielding materials,which can be used for the electromagne...Highly conductive polymer composites(CPCs) with excellent mechanical flexibility are ideal materials for designing excellent electromagnetic interference(EMI) shielding materials,which can be used for the electromagnetic interference protection of flexible electronic devices.It is extremely urgent to fabricate ultra-strong EMI shielding CPCs with efficient conductive networks.In this paper,a novel silver-plated polylactide short fiber(Ag@PL ASF,AAF) was fabricated and was integrated with carbon nanotubes(CNT) to construct a multi-scale conductive network in polydimethylsiloxane(PDMS) matrix.The multi-scale conductive network endowed the flexible PDMS/AAF/CNT composite with excellent electrical conductivity of 440 S m-1and ultra-strong EMI shielding effectiveness(EMI SE) of up to 113 dB,containing only 5.0 vol% of AAF and 3.0 vol% of CNT(11.1wt% conductive filler content).Due to its excellent flexibility,the composite still showed 94% and 90% retention rates of EMI SE even after subjected to a simulated aging strategy(60℃ for 7 days) and 10,000 bending-releasing cycles.This strategy provides an important guidance for designing excellent EMI shielding materials to protect the workspace,environment and sensitive circuits against radiation for flexible electronic devices.展开更多
The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and v...The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.展开更多
System reliability can produce a strong influence on the performance of the heat exchanger network(HEN).In this paper,an optimization method with system reliability analysis for flexible HEN by genetic/simulated annea...System reliability can produce a strong influence on the performance of the heat exchanger network(HEN).In this paper,an optimization method with system reliability analysis for flexible HEN by genetic/simulated annealing algorithms(GA/SA) is presented.Initial flexible arrangements of HEN is received by pseudo-temperature enthalpy diagram.For determining system reliability of HEN,the connections of heat exchangers(HEXs) and independent subsystems in the HEN are analyzed by the connection sequence matrix(CSM),and the system reliability is measured by the independent subsystem including maximum number of HEXs in the HEN.As for the HEN that did not meet system reliability,HEN decoupling is applied and the independent subsystems in the HEN are changed by removing decoupling HEX,and thus the system reliability is elevated.After that,heat duty redistribution based on the relevant elements of the heat load loops and HEX areas are optimized in GA/SA.Then,the favorable network configuration,which matches both the most economical cost and system reliability criterion,is located.Moreover,particular features belonging to suitable decoupling HEX are extracted from calculations.Corresponding numerical example is presented to verify that the proposed strategy is effective to formulate optimal flexible HEN with system reliability measurement.展开更多
Wearable flexible sensors attached on the neck have been developed to measure the vibration of vocal cords during speech.However,highfrequency attenuation caused by the frequency response of the flexible sensors and a...Wearable flexible sensors attached on the neck have been developed to measure the vibration of vocal cords during speech.However,highfrequency attenuation caused by the frequency response of the flexible sensors and absorption of high-frequency sound by the skin are obstacles to the practical application of these sensors in speech capture based on bone conduction.In this paper,speech enhancement techniques for enhancing the intelligibility of sensor signals are developed and compared.Four kinds of speech enhancement algorithms based on a fully connected neural network(FCNN),a long short-term memory(LSTM),a bidirectional long short-term memory(BLSTM),and a convolutional-recurrent neural network(CRNN)are adopted to enhance the sensor signals,and their performance after deployment on four kinds of edge and cloud platforms is also investigated.Experimental results show that the BLSTM performs best in improving speech quality,but is poorest with regard to hardware deployment.It improves short-time objective intelligibility(STOI)by 0.18 to nearly 0.80,which corresponds to a good intelligibility level,but it introduces latency as well as being a large model.The CRNN,which improves STOI to about 0.75,ranks second among the four neural networks.It is also the only model that is able to achieves real-time processing with all four hardware platforms,demonstrating its great potential for deployment on mobile platforms.To the best of our knowledge,this is one of the first trials to systematically and specifically develop processing techniques for bone-conduction speed signals captured by flexible sensors.The results demonstrate the possibility of realizing a wearable lightweight speech collection system based on flexible vibration sensors and real-time speech enhancement to compensate for high-frequency attenuation.展开更多
Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters haveoccurred almost annu...Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters haveoccurred almost annuallyinthe urban area of Beijing, the capital of China. Based on a selforganizing map(SOM) artificial neural network(ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product(GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANNis suitable for automatically and quantitatively assessing risks associated with waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors,producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. The points that were assigned risk grades of IV or Vwere located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.展开更多
In space operation,flexible manipulators and gripper mechanisms have been widely used because of light weight and flexibility.However,the vibration caused by slender structures in manipulators and the parameter pertur...In space operation,flexible manipulators and gripper mechanisms have been widely used because of light weight and flexibility.However,the vibration caused by slender structures in manipulators and the parameter perturbation caused by the uncertainty derived from grasping mass variation cannot be ignored.The existence of vibration and parameter perturbation makes the rotation control of flexible manipulators difficult,which seriously affects the operation accuracy of manipulators.What’s more,the complex dynamic coupling brings great challenges to the dynamics modeling and vibration analysis.To solve this problem,this paper takes the space flexible manipulator with an underactuated hand(SFMUH)as the research object.The dynamics model considering flexibility,multiple nonlinear elements and disturbance torque is established by the assumed modal method(AMM)and Hamilton’s principle.A dynamic modeling simplification method is proposed by analyzing the nonlinear terms.What’s more,a sliding mode control(SMC)method combined with the radial basis function(RBF)neural network compensation is proposed.Besides,the control law is designed using a saturation function in the control method to weaken the chatter phenomenon.With the help of neural networks to identify the uncertainty composition in the SFMUH,the tracking accuracy is improved.The results of ground control experiments verify the advantages of the control method for vibration suppression of the SFMUH.展开更多
Internet of things and network densification bring significant challenges to uplink management.Only depending on optimization algorithm enhancements is not enough for uplink transmission.To control intercell interfere...Internet of things and network densification bring significant challenges to uplink management.Only depending on optimization algorithm enhancements is not enough for uplink transmission.To control intercell interference,Fractional Uplink Power Control(FUPC)should be optimized from network-wide perspective,which has to find a better traffic distribution model.Conventionally,traffic distribution is geographic-based,and ineffective due to tricky locating efforts.This paper proposes a novel uplink power management framework for Self-Organizing Networks(SON),which firstly builds up pathloss-based traffic distribution model and then makes the decision of FUPC based on the model.PathLoss-based Traffic Distribution(PLTD)aggregates traffic based on the propagation condition of traffic that is defined as the pathloss between the position generating the traffic and surrounding cells.Simulations show that the improvement in optimization efficiency of FUPC with PLTD can be up to 40%compared to conventional GeoGraphic-based Traffic Distribution(GGTD).展开更多
Energy efficiency is a primary consideration in a wireless sensor network (WSN). This is also a major parameter when designing a medium access control (MAC) protocol for WSNs. Hierarchical clustering structure is rega...Energy efficiency is a primary consideration in a wireless sensor network (WSN). This is also a major parameter when designing a medium access control (MAC) protocol for WSNs. Hierarchical clustering structure is regarded suitable for WSNs due to its good performance in energy conservation. In this work, an adequately flexible mechanism for clustering WSNs is designed, in which some creative or promotional metrics are utilized, such as cluster head selection algorithm, cluster optional reconstruction, interested data transmission, multiple path routing protocol. All these strategies were cooperated to maximize energy saving of whole system. An appropriate MAC protocol for this mechanism is proposed, by flexibly switching the status of diverse sensor nodes in different strategies. The simulation results show that the proposed MAC protocol is suitable for clustering WSNs and performs well in aspects of energy efficiency, flexibility and scalability.展开更多
An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attach...An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy.展开更多
Entrepreneurship corporate social responsibility is concerned with obligations that should be undertaken by an enterprise or ＂enterprise citizen＂ to the society including interrelationship between enterprise and som...Entrepreneurship corporate social responsibility is concerned with obligations that should be undertaken by an enterprise or ＂enterprise citizen＂ to the society including interrelationship between enterprise and some related interest dependents. And it is a sense of value, discipline and respect to the people, community and environment-related policies of the enterprise. Obviously, the core of the notion refers to a commitment of the enterprise in order to improve living standard of related interest counterparts. Nowadays, entrepreneurship corporate social responsibility has been not only an ethical call, but also an institutional constraint. The consensus is that in operation process an enterprise should take into account of its economic, social and ethical effects on consumers, staffs, shareholders, communities, local governments and environment and make a better prospect to them. Based on this point of view, by field work and questionnaire method, this paper discusses specifically the interaction between TNCs＇ R＆D activities and local development of the Pudong New Area, a China＇s largest special economic zone in Shanghai to explore dynamics of the TNCs＇ R＆D activities, growth of the local economy and their roles in promoting flexible innovation networks for sustainable futures. This involves： a. notion of the entrepreneurship corporate social responsibility; b. current state and trend of TNCs＇ R＆D activities; c. mode and linkage tightness between TNCs＇ R＆D activities and the local economy; d. main problems of the TNCs＇ R＆D activities in Pudong; e. the context of flexible innovation networks; and f. manner and ways in creation of flexible innovation networks.展开更多
Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from ...Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter selection.This paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic algorithms.Simulations show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm accuracy.Compared with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.展开更多
基金supported by the National Natural Science Foundation of China(No.62401597)the Natural Science Foundation of Hunan Province,China(No.2024JJ6469)the Scientific Research Project of National University of Defense Technology,China(No.ZK22-02)。
文摘The information exchange among satellites is crucial for the implementation of cluster satellite cooperative missions.However,achieving fast perception,rapid networking,and highprecision time synchronization among nodes without the support of the Global Navigation Satellite System(GNSS)and other prior information remains a formidable challenge to real-time wireless networks design.Therefore,a self-organizing network methodology based on multi-agent negotiation is proposed,which autonomously determines the master node through collaborative negotiation and competitive elections.On this basis,a real-time network protocol design is carried out and a high-precision time synchronization method with motion compensation is proposed.Simulation results demonstrate that the proposed method enables rapid networking with the capability of selfdiscovery,self-organization,and self-healing.For a cluster of 8 satellites,the networking time and the reorganization time are less than 4 s.The time synchronization accuracy exceeds 10-10s with motion compensation,demonstrating excellent real-time performance and stability.The research presented in this paper provides a valuable reference for the design and application of spacebased self-organizing networks for satellite cluster.
基金supported in part by National Natural Science Foundation of China under Grant 52007026.
文摘With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FDN),the calculation of carbon flow distribution in FDN is more difficult.To this end,this study constructs a model for low-carbon optimal operations within the FDN on the basis of enhanced carbon emission flow(CEF).First,the carbon emission characteristics of FDNs are scrutinized and an improved method for calculating carbon flow within these networks is proposed.Subsequently,a model for optimizing low-carbon operations within FDNs is formulated based on the refined CEF,which merges the specificities of DG and intelligent SOP.Finally,this model is scrutinized using an upgraded IEEE 33-node distribution system,a comparative analysis of the cases reveals that when DG and SOP are operated in a coordinated manner in the FDN,with the cost of electricity generation was reduced by 40.63 percent and the cost of carbon emissions by 10.18 percent.The findings indicate that the judicious optimization of areas exhibiting higher carbon flow rates can effectively enhance the economic efficiency of DN operations and curtail the carbon emissions of the overall network.
基金Supported by the National Natural Science Foundation of China(21676211,21878240,21808179)China’s Post-doctoral Science Fund(2018M633518)+1 种基金Key Research and Development Program of Shaanxi Province(2018GY-072)the Fundamental Research Funds for the Central Universities(1191329819)
文摘Dealing with uncertainty is one of practical issues in design and operation of heat exchanger networks(HENs),arising the problem of flexible HEN synthesis.This paper addresses the state-of-the-art methods for flexible HEN synthesis based on sensitivity analysis,resilience analysis,flexibility analysis and multiperiod synthesis techniques as well.Each of these methods is summarized by presenting their general procedures and recent developments on modeling,solving strategies and applications.Some current topics related to flexible process synthesis have been briefly presented to provide several future research possibilities.
基金supported by National Natural Science Foundation of China(No.61703402)
文摘This paper mainly focuses on designing a sliding mode boundary controller for a single flexible-link manipulator based on adaptive radial basis function （RBF） neural network. The flexible manipulator in this paper is considered to be an Euler-Bernoulli beam. We first obtain a partial differential equation （PDE） model of single-link flexible manipulator by using Hamiltons approach. To improve the control robustness, the system uncertainties including modeling uncertainties and external disturbances are compensated by an adaptive neural approximator. Then, a sliding mode control method is designed to drive the joint to a desired position and rapidly suppress vibration on the beam. The stability of the closed-loop system is validated by using Lyapunov＇s method based on infinite dimensional model, avoiding problems such as control spillovers caused by traditional finite dimensional truncated models. This novel controller only requires measuring the boundary information, which facilitates implementation in engineering practice. Favorable performance of the closed-loop system is demonstrated by numerical simulations.
基金Project supported by the Key Project(No.60934001)the General Projects(Nos.51175181and90505014)of the National Natural Science Foundation of Chinaby the Fundamental Research Funds for the Central Universities,SCUT(No.2012ZZ0060)
文摘This paper aims at modeling and developing vibration control methods for a flexible piezoelectric beam. A collocated sensor/actuator placement is used. Finite element analysis （FEA） method is adopted to derive the dynamics model of the system. A back propagation neural network （BPNN） based proportional-derivative （PD） algorithm is applied to suppress the vibration. Simulation and experiments are conducted using the FEA model and BPNN-PD control law. Experimental results show good agreement with the simulation results using finite element modeling and the neural network control algorithm.
基金Supported by the National Natural Science Foundation of China （20976022） and Dalian University of Technology for Constructing Interdiscipline ＇Energy＋X＇. ACKNOWLEDGEMENTS The authors gratefully acknowledge financial support from Lanzhou Petrochemical Company, PetroChina Company Limited.
文摘A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network(HEN)by genetic/simulated annealing algorithms(GA/SA).Through taking into account the effect of fouling process on optimal network topology,a preliminary network structure possessing two-fold oversynthesis is obtained by means of pseudo-temperature enthalpy(T-H)diagram approach prior to simultaneous optimization.Thus,the computational complexity of this problem classified as NP(Non-deterministic Polynomial)-complete can be significantly reduced.The promising matches resulting from preliminary synthesis stage are further optimized in parallel with their heat exchange areas and cleaning schedule.In addition,a novel continu- ous time representation is introduced to subdivide the given time horizon into several variable-size intervals according to operating periods of heat exchangers,and then flexible HEN synthesis can be implemented in dynamic manner.A numerical example is provided to demonstrate that the presented strategy is feasible to decrease the total annual cost(TAC)and further improve network flexibility,but even more important,it may be applied to solve large-scale flexible HEN synthesis problems.
基金Supported by National Natural Science Foundation of China(Grant No.51875092)National Key Research and Development Project of China(Grant No.2020YFB2007802)+1 种基金Natural Science Foundation of Ningxia Province(Grant No.2020AAC03279)Fundamental Research Funds for the Central Universities(Grant No.N2103025).
文摘The length of fexible manipulators with a telescopic arm alters during movement.The dynamic parameters of telescopic fexible manipulators exhibit signifcant time-varying characteristics owing to variations in length.With an increase in the manipulators’length,the nonlinear terms caused by fexibility in the manipulators’dynamic equations cannot be ignored.The time-varying characteristics and nonlinear terms of telescopic fexible manipulators cause fuctuations in rotation angles,which afect the operation accuracy of end-efectors.In this study,a control strategy based on a combination of fuzzy adjustment and an RBF neural network is utilized to improve the control accuracy of fexible telescopic manipulators.First,the dynamic equation of the manipulators is established using the assumed mode method and Lagrange’s principle,and the infuence of nonlinear terms is analyzed.Subsequently,a combined control strategy is proposed to suppress the fuctuation of the rotation angle in telescopic fexible manipulators.The variation ranges of the feedforward PD controller parameters are determined by the pole placement strategy and length of the manipulators.Fuzzy rules are utilized to adjust the controller parameters in real-time.The RBF neural network is utilized to identify and compensate the uncertain part of the dynamic model of the fexible manipulators.The uncertain part comprises time-varying parameters and nonlinear terms.Finally,numerical simulations and prototype experiments prove the efectiveness of the combined control strategy.The results prove that the proposed control strategy has a smaller standard deviation of errors.Therefore,the combined control strategy is more suitable for telescopic fexible manipulators,which can efectively improve the control accuracy of rotation angles.
文摘Due to the widespread use of the Internet,customer information is vulnerable to computer systems attack,which brings urgent need for the intrusion detection technology.Recently,network intrusion detection has been one of the most important technologies in network security detection.The accuracy of network intrusion detection has reached higher accuracy so far.However,these methods have very low efficiency in network intrusion detection,even the most popular SOM neural network method.In this paper,an efficient and fast network intrusion detection method was proposed.Firstly,the fundamental of the two different methods are introduced respectively.Then,the selforganizing feature map neural network based on K-means clustering(KSOM)algorithms was presented to improve the efficiency of network intrusion detection.Finally,the NSLKDD is used as network intrusion data set to demonstrate that the KSOM method can significantly reduce the number of clustering iteration than SOM method without substantially affecting the clustering results and the accuracy is much higher than Kmeans method.The Experimental results show that our method can relatively improve the accuracy of network intrusion and significantly reduce the number of clustering iteration.
基金supported by the National Natural Science Foundation of China(Nos.51973142,52033005,52003169).
文摘Highly conductive polymer composites(CPCs) with excellent mechanical flexibility are ideal materials for designing excellent electromagnetic interference(EMI) shielding materials,which can be used for the electromagnetic interference protection of flexible electronic devices.It is extremely urgent to fabricate ultra-strong EMI shielding CPCs with efficient conductive networks.In this paper,a novel silver-plated polylactide short fiber(Ag@PL ASF,AAF) was fabricated and was integrated with carbon nanotubes(CNT) to construct a multi-scale conductive network in polydimethylsiloxane(PDMS) matrix.The multi-scale conductive network endowed the flexible PDMS/AAF/CNT composite with excellent electrical conductivity of 440 S m-1and ultra-strong EMI shielding effectiveness(EMI SE) of up to 113 dB,containing only 5.0 vol% of AAF and 3.0 vol% of CNT(11.1wt% conductive filler content).Due to its excellent flexibility,the composite still showed 94% and 90% retention rates of EMI SE even after subjected to a simulated aging strategy(60℃ for 7 days) and 10,000 bending-releasing cycles.This strategy provides an important guidance for designing excellent EMI shielding materials to protect the workspace,environment and sensitive circuits against radiation for flexible electronic devices.
基金supported by the Science and Technology Support Program of Guizhou Province([2022]General 012)the Key Science and Technology Project of China Southern Power Grid Corporation(GZKJXM20220043)。
文摘The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.
文摘System reliability can produce a strong influence on the performance of the heat exchanger network(HEN).In this paper,an optimization method with system reliability analysis for flexible HEN by genetic/simulated annealing algorithms(GA/SA) is presented.Initial flexible arrangements of HEN is received by pseudo-temperature enthalpy diagram.For determining system reliability of HEN,the connections of heat exchangers(HEXs) and independent subsystems in the HEN are analyzed by the connection sequence matrix(CSM),and the system reliability is measured by the independent subsystem including maximum number of HEXs in the HEN.As for the HEN that did not meet system reliability,HEN decoupling is applied and the independent subsystems in the HEN are changed by removing decoupling HEX,and thus the system reliability is elevated.After that,heat duty redistribution based on the relevant elements of the heat load loops and HEX areas are optimized in GA/SA.Then,the favorable network configuration,which matches both the most economical cost and system reliability criterion,is located.Moreover,particular features belonging to suitable decoupling HEX are extracted from calculations.Corresponding numerical example is presented to verify that the proposed strategy is effective to formulate optimal flexible HEN with system reliability measurement.
基金This work was supported in part by the Key Research and Development Program of Zhejiang Province,China(Grant No.2021C05005)the National Natural Science Foundation of China(Grant No.81771880)the Tianjin Municipal Government of China(Grant No.19JCQNJC12800).
文摘Wearable flexible sensors attached on the neck have been developed to measure the vibration of vocal cords during speech.However,highfrequency attenuation caused by the frequency response of the flexible sensors and absorption of high-frequency sound by the skin are obstacles to the practical application of these sensors in speech capture based on bone conduction.In this paper,speech enhancement techniques for enhancing the intelligibility of sensor signals are developed and compared.Four kinds of speech enhancement algorithms based on a fully connected neural network(FCNN),a long short-term memory(LSTM),a bidirectional long short-term memory(BLSTM),and a convolutional-recurrent neural network(CRNN)are adopted to enhance the sensor signals,and their performance after deployment on four kinds of edge and cloud platforms is also investigated.Experimental results show that the BLSTM performs best in improving speech quality,but is poorest with regard to hardware deployment.It improves short-time objective intelligibility(STOI)by 0.18 to nearly 0.80,which corresponds to a good intelligibility level,but it introduces latency as well as being a large model.The CRNN,which improves STOI to about 0.75,ranks second among the four neural networks.It is also the only model that is able to achieves real-time processing with all four hardware platforms,demonstrating its great potential for deployment on mobile platforms.To the best of our knowledge,this is one of the first trials to systematically and specifically develop processing techniques for bone-conduction speed signals captured by flexible sensors.The results demonstrate the possibility of realizing a wearable lightweight speech collection system based on flexible vibration sensors and real-time speech enhancement to compensate for high-frequency attenuation.
基金supported by the National Key R&D Program of China (GrantN o.2016YFC0401407)National Natural Science Foundation of China (Grant Nos. 51479003 and 51279006)
文摘Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters haveoccurred almost annuallyinthe urban area of Beijing, the capital of China. Based on a selforganizing map(SOM) artificial neural network(ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product(GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANNis suitable for automatically and quantitatively assessing risks associated with waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors,producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. The points that were assigned risk grades of IV or Vwere located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.
基金supported by the National Natural Science Foundation of China(No.52275090)the Fundamental Research Funds for the Central Universities(No.N2103025)+1 种基金the National Key Research and Development Program of China(No.2020YFB2007802)the Applied Basic Research Program of Liaoning Province(No.2023JH2/101300159)。
文摘In space operation,flexible manipulators and gripper mechanisms have been widely used because of light weight and flexibility.However,the vibration caused by slender structures in manipulators and the parameter perturbation caused by the uncertainty derived from grasping mass variation cannot be ignored.The existence of vibration and parameter perturbation makes the rotation control of flexible manipulators difficult,which seriously affects the operation accuracy of manipulators.What’s more,the complex dynamic coupling brings great challenges to the dynamics modeling and vibration analysis.To solve this problem,this paper takes the space flexible manipulator with an underactuated hand(SFMUH)as the research object.The dynamics model considering flexibility,multiple nonlinear elements and disturbance torque is established by the assumed modal method(AMM)and Hamilton’s principle.A dynamic modeling simplification method is proposed by analyzing the nonlinear terms.What’s more,a sliding mode control(SMC)method combined with the radial basis function(RBF)neural network compensation is proposed.Besides,the control law is designed using a saturation function in the control method to weaken the chatter phenomenon.With the help of neural networks to identify the uncertainty composition in the SFMUH,the tracking accuracy is improved.The results of ground control experiments verify the advantages of the control method for vibration suppression of the SFMUH.
文摘Internet of things and network densification bring significant challenges to uplink management.Only depending on optimization algorithm enhancements is not enough for uplink transmission.To control intercell interference,Fractional Uplink Power Control(FUPC)should be optimized from network-wide perspective,which has to find a better traffic distribution model.Conventionally,traffic distribution is geographic-based,and ineffective due to tricky locating efforts.This paper proposes a novel uplink power management framework for Self-Organizing Networks(SON),which firstly builds up pathloss-based traffic distribution model and then makes the decision of FUPC based on the model.PathLoss-based Traffic Distribution(PLTD)aggregates traffic based on the propagation condition of traffic that is defined as the pathloss between the position generating the traffic and surrounding cells.Simulations show that the improvement in optimization efficiency of FUPC with PLTD can be up to 40%compared to conventional GeoGraphic-based Traffic Distribution(GGTD).
文摘Energy efficiency is a primary consideration in a wireless sensor network (WSN). This is also a major parameter when designing a medium access control (MAC) protocol for WSNs. Hierarchical clustering structure is regarded suitable for WSNs due to its good performance in energy conservation. In this work, an adequately flexible mechanism for clustering WSNs is designed, in which some creative or promotional metrics are utilized, such as cluster head selection algorithm, cluster optional reconstruction, interested data transmission, multiple path routing protocol. All these strategies were cooperated to maximize energy saving of whole system. An appropriate MAC protocol for this mechanism is proposed, by flexibly switching the status of diverse sensor nodes in different strategies. The simulation results show that the proposed MAC protocol is suitable for clustering WSNs and performs well in aspects of energy efficiency, flexibility and scalability.
基金Supported by National Natural Science Foundation of China(No.59975001 and 50205019).
文摘An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy.
文摘Entrepreneurship corporate social responsibility is concerned with obligations that should be undertaken by an enterprise or ＂enterprise citizen＂ to the society including interrelationship between enterprise and some related interest dependents. And it is a sense of value, discipline and respect to the people, community and environment-related policies of the enterprise. Obviously, the core of the notion refers to a commitment of the enterprise in order to improve living standard of related interest counterparts. Nowadays, entrepreneurship corporate social responsibility has been not only an ethical call, but also an institutional constraint. The consensus is that in operation process an enterprise should take into account of its economic, social and ethical effects on consumers, staffs, shareholders, communities, local governments and environment and make a better prospect to them. Based on this point of view, by field work and questionnaire method, this paper discusses specifically the interaction between TNCs＇ R＆D activities and local development of the Pudong New Area, a China＇s largest special economic zone in Shanghai to explore dynamics of the TNCs＇ R＆D activities, growth of the local economy and their roles in promoting flexible innovation networks for sustainable futures. This involves： a. notion of the entrepreneurship corporate social responsibility; b. current state and trend of TNCs＇ R＆D activities; c. mode and linkage tightness between TNCs＇ R＆D activities and the local economy; d. main problems of the TNCs＇ R＆D activities in Pudong; e. the context of flexible innovation networks; and f. manner and ways in creation of flexible innovation networks.
基金the National Natural Science Foundation of China (No.61627810)the National Science and Technology Major Program of China (No.2018YFB1305003)the National Defense Science and Technology Outstanding Youth Science Foundation (No.2017-JCJQ-ZQ-031)。
文摘Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization prob-lem.Based on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter selection.This paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic algorithms.Simulations show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm accuracy.Compared with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.
