A method for determining symbolic and all numerical solutions in design optimization based on monotonicity analysis and solving polynomial systems is presented in this paper. Groebner Bases of the algebraic system equ...A method for determining symbolic and all numerical solutions in design optimization based on monotonicity analysis and solving polynomial systems is presented in this paper. Groebner Bases of the algebraic system equivalent to the subproblem of the design optimization is taken as the symbolic (analytical) expression of the optimum solution for the symbolic optimization, i.e. the problem with symbolic coefficients. A method based on substituting and eliminating for determining Groebner Bases is also proposed, and method for finding all numerical optimum solutions is discussed. Finally an example is given, demonstrating the strategy and efficiency of the method.展开更多
Swiss FEL is a free electron laser(FEL) under commissioning at the Paul Scherrer Institut(PSI) in Switzerland. Digital low-level RF(LLRF) systems are used in Swiss FEL to control more than 30 RF stations with either s...Swiss FEL is a free electron laser(FEL) under commissioning at the Paul Scherrer Institut(PSI) in Switzerland. Digital low-level RF(LLRF) systems are used in Swiss FEL to control more than 30 RF stations with either standing wave cavities(e.g. RF gun) or travelling wave structures working at different frequencies. After conditioned to desired power levels, the RF stations need to be setup for beam operation and the LLRF parameters need to be optimized for maximizing the beam stability. Several beam-based algorithms were developed to facilitate the setup, calibration and optimization of the Swiss FEL RF stations for beam operation. The algorithms were implemented as automation procedures in the framework of Experimental Physics and Industrial Control System(EPICS) and were used in commissioning and daily operation of Swiss FEL. In this paper, the algorithms and the implementation will be introduced together with the test results during the commissioning of SwissFEL.展开更多
Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damp...Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damper dynamic model.Certain standards for both take-off and landing performance are put forward.The contradictory factors between take-off and landing processes are analyzed.The optimization of oil in the pin area and the area near the rear oil hole is performed.Then these optimized parameters are used to assess the influence of the initial pressure of the low chamber,the ratio of the high chamber to the low chamber,and the tire inflation pressure on the performance of arresting landing and catapult take-off.The influences of these parameters on carrier-based aircraft and the aircraft-carrier on aircraft catapult take-off is also assessed.Based on the results of the simulation,respective take-off criteria must be drafted considering different types of aircraft and different take-off load cases,all of which must be matched to parameters relevant to catapult take-off.展开更多
A constrained multi-objective biogeography-based optimization algorithm （CMBOA） was proposed to solve robot path planning （RPP）. For RPP, the length and smoothness of path were taken as the optimization objectives...A constrained multi-objective biogeography-based optimization algorithm （CMBOA） was proposed to solve robot path planning （RPP）. For RPP, the length and smoothness of path were taken as the optimization objectives, and the distance from the obstacles was constraint. In CMBOA, a new migration operator with disturbance factor was designed and applied to the feasible population to generate many more non-dominated feasible individuals; meanwhile, some infeasible individuals nearby feasible region were recombined with the nearest feasible ones to approach the feasibility. Compared with classical multi-objective evolutionary algorithms, the current study indicates that CM- BOA has better performance for RPP.展开更多
Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is p...Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is proposed. Specific improvements includes:(1)An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining.(2) A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms,this study verifies that WOA-MS has an excellent optimization performance.展开更多
There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based ...There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based on algorithms and hardware selections with insufficient physical information. We present such an energy model for typical base stations. This model can help designers in estimating, evaluating and optimizing energy/power consumption of candidate designs in early design stages. The proposed model is verified by an LTE extreme scenario. The estimated results show that digital front-end, channel equalization and channel decoding are three major power greedy modules(consuming 39.4%, 16.3%, 13.4%) in a digital baseband subsystem. The power estimation error of the proposed power amplifier(PA) power model is 3.5%(macro cell). The major contribution of this paper is that the proposed models can rapidly estimate energy/power consumption of 4G and the future base stations(such as 5G) in early design stages with well acceptable precision, even without sufficient implementation information.展开更多
Carrier-based aircraft carrier landing is a special kind of tracking control problem and not suitable for classical control methods,which may miss the desired performance or result in overdesign.Therefore,we present a...Carrier-based aircraft carrier landing is a special kind of tracking control problem and not suitable for classical control methods,which may miss the desired performance or result in overdesign.Therefore,we present an optimal preview control for automatic carrier landing system(ACLS)by using state information of system,as well as future reference information,which can avoid the shortcomings of classical control methods.Since the flight performance of carrier-based aircraft is disturbed by air wake when the aircraft flies near the area of carrier stern,we design a disturbance rejection strategy to ensure that aircraft track the glide path with high precision and robustness.Further,carrier-based aircraft is a complex nonlinear system.However,the nonlinear model of carrier-based aircraft can be linearized at equilibrium landing state and decoupled into the longitudinal model and the lateral model.Therefore,an optimal preview control system is designed.The simulation results of a carrier-based aircraft show that the optimal preview control system can effectively suppress air wake.Tracking accuracy of optimal preview controller is higher than that of the proportional integral differential(PID)control system.展开更多
Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base statio...Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.展开更多
The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries.To maximize overall benefits for the investors and operators of base ...The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries.To maximize overall benefits for the investors and operators of base station energy storage,we proposed a bi-level optimization model for the operation of the energy storage,and the planning of 5G base stations considering the sleep mechanism.A multi-base station cooperative system composed of 5G acer stations was considered as the research object,and the outer goal was to maximize the net profit over the complete life cycle of the energy storage.Furthermore,the power and capacity of the energy storage configuration were optimized.The inner goal included the sleep mechanism of the base station,and the optimization of the energy storage charging and discharging strategy,for minimizing the daily electricity expenditure of the 5G base station system.Additionally,genetic algorithm and mixed integer programming were used to solve the bi-level optimization model,analyze the numerical example test comparison of the three types of batteries and the net income of the configuration,and finally verify the validity of the model.Furthermore,the sleep mechanism,the charging and discharging strategy for energy consumption,and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration.展开更多
Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequenc...Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.展开更多
A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate...A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate flight pairs were selected from all international flights arriving at or departing from China in one day according to the requirement of the proposed method.Aircraft performance database Base of Aircraft Data(BADA)was employed in the trajectory computation.By assuming different fuel-saving percentages for the following aircraft,pre-flight plan trajectories of formation flight were optimized.The fuel consumption optimization effect under the influence of different trajectory optimization parameters was also analyzed.The results showed that the higher the fuel savings percentage,the longer the flight distance of formation flight,but the smaller the number of formation combinations that can be realized,which is limited by the aircraft performance.The following aircraft flying along the approximate actual flight trajectory can be benefited as well,and the optimal fuel-saving efficiency is related to the expected fuelsaving efficiency of formation flight.展开更多
The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis a...The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis and prognosis, and maintenance optimization. Relevant academic research and industrial applications are identified and summarized. The state of art, capabilities,and constraints of condition-based maintenance are analyzed. The presented research demonstrates that the intelligent-based approach has become a promising solution for condition recognition, and an integrated data platform for offshore wind farms is significant to optimize the maintenance activities.展开更多
For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.How...For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.展开更多
The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.Th...The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.The program of genetic algorithm is developed by the authors while the gradient-based algorithm borrows from the modified method for feasible direction in MSC/NASTRAN software.In the hybrid algorithm,the genetic algorithm is used to perform global search to avoid to fall into local optima,and then the excellent individuals of every generation optimized by the genetic algorithm are further fine-tuned by the modified method for feasible direction to attain the local optima and hence to get global optima.Moreover,the application effects of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft wing are discussed,which satisfy multiple constraints of strength,displacement,aileron efficiency,and flutter speed.The application results show that the genetic/gradient-based hybrid algorithm is available for aeroelastic optimization of large aircraft wings in initial design phase as well as detailed design phase,and the optimization results are very consistent.Therefore,the design modifications can be decreased using the genetic/gradient-based hybrid algorithm.展开更多
Autonomous Underwater Vehicles （AUVs） are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. T...Autonomous Underwater Vehicles （AUVs） are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. This framework enhances AUV mission performance by completing the maximum number of highest priority tasks in a limited time through a large-scale waypoint cluttered operating field and ensuring safe deployment during the mission. The proposed combinatorial route-path-planner model takes advantage of the Biogeography- Based Optimization （BBO） algorithm to satisfy the objectives of both higher- and lower-level motion planners and guarantee the maximization of mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios, including cost constraints in time-varying operating fields. To demonstrate the reliability of the proposed model, the performance of each motion planner is separately assessed and statistical analysis is conducted to evaluate the total performance of the entire model. The simulation results indicate the stability of the proposed model and the feasibility of its application to real-time experiments.展开更多
In our former work [Catal. Today 174 （2011） 127], 12 heterogeneous catalysts were screened for CO oxidation, and Au-ZnO/Al2O3 was chosen and optimized in terms of weight loadings of Au and ZnO. The present study fol...In our former work [Catal. Today 174 （2011） 127], 12 heterogeneous catalysts were screened for CO oxidation, and Au-ZnO/Al2O3 was chosen and optimized in terms of weight loadings of Au and ZnO. The present study follows on to consider the impact of process parameters （catalyst preparation and reaction conditions）, in conjunction with catalyst composition （weight loadings of Au and ZnO, and the total weight of the catalyst）, as the optimization of the process parameters simultaneously optimized the catalyst composition. The optimization target is the reactivity of this important reaction. These factors were first optimized using response surface methodology （RSM） with 25 experiments, to obtain the optimum： 100 mg of 1.0%Au-4.1%ZnO/Al2O3 catalyst with 220℃ calcination and 100℃ reduction. After optimization, the main effects and interactions of these five factors were studied using statistical sensitivity analysis （SA）. Certain observations from SA were verified by reaction mechanism, reactivity test and/or characterization techniques, while others need further investigation.展开更多
Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thres...Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.展开更多
文摘A method for determining symbolic and all numerical solutions in design optimization based on monotonicity analysis and solving polynomial systems is presented in this paper. Groebner Bases of the algebraic system equivalent to the subproblem of the design optimization is taken as the symbolic (analytical) expression of the optimum solution for the symbolic optimization, i.e. the problem with symbolic coefficients. A method based on substituting and eliminating for determining Groebner Bases is also proposed, and method for finding all numerical optimum solutions is discussed. Finally an example is given, demonstrating the strategy and efficiency of the method.
文摘Swiss FEL is a free electron laser(FEL) under commissioning at the Paul Scherrer Institut(PSI) in Switzerland. Digital low-level RF(LLRF) systems are used in Swiss FEL to control more than 30 RF stations with either standing wave cavities(e.g. RF gun) or travelling wave structures working at different frequencies. After conditioned to desired power levels, the RF stations need to be setup for beam operation and the LLRF parameters need to be optimized for maximizing the beam stability. Several beam-based algorithms were developed to facilitate the setup, calibration and optimization of the Swiss FEL RF stations for beam operation. The algorithms were implemented as automation procedures in the framework of Experimental Physics and Industrial Control System(EPICS) and were used in commissioning and daily operation of Swiss FEL. In this paper, the algorithms and the implementation will be introduced together with the test results during the commissioning of SwissFEL.
基金supported by the National Natural Science Foundation of China(Nos.5130519811372129)
文摘Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damper dynamic model.Certain standards for both take-off and landing performance are put forward.The contradictory factors between take-off and landing processes are analyzed.The optimization of oil in the pin area and the area near the rear oil hole is performed.Then these optimized parameters are used to assess the influence of the initial pressure of the low chamber,the ratio of the high chamber to the low chamber,and the tire inflation pressure on the performance of arresting landing and catapult take-off.The influences of these parameters on carrier-based aircraft and the aircraft-carrier on aircraft catapult take-off is also assessed.Based on the results of the simulation,respective take-off criteria must be drafted considering different types of aircraft and different take-off load cases,all of which must be matched to parameters relevant to catapult take-off.
基金Supported by the National Natural Science Foundation of Chi- na（61075113） the Excellent Young Teacher Foundation of Heilongjiang Province of China （1155G18） the Fundamental Research Funds for the Central Universities （HEUCFZl209）
文摘A constrained multi-objective biogeography-based optimization algorithm （CMBOA） was proposed to solve robot path planning （RPP）. For RPP, the length and smoothness of path were taken as the optimization objectives, and the distance from the obstacles was constraint. In CMBOA, a new migration operator with disturbance factor was designed and applied to the feasible population to generate many more non-dominated feasible individuals; meanwhile, some infeasible individuals nearby feasible region were recombined with the nearest feasible ones to approach the feasibility. Compared with classical multi-objective evolutionary algorithms, the current study indicates that CM- BOA has better performance for RPP.
基金supported by the Natural Science Foundation of Jiangsu Province (No. BK20151479)the Open Foundation of Graduate Innovation Base in Nanjing University of Aeronautics and Astronautics(No. kfjj20190736)
文摘Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is proposed. Specific improvements includes:(1)An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining.(2) A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms,this study verifies that WOA-MS has an excellent optimization performance.
基金supporting from National High Technical Research and Development Program of China (863 program) 2014AA01A705
文摘There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based on algorithms and hardware selections with insufficient physical information. We present such an energy model for typical base stations. This model can help designers in estimating, evaluating and optimizing energy/power consumption of candidate designs in early design stages. The proposed model is verified by an LTE extreme scenario. The estimated results show that digital front-end, channel equalization and channel decoding are three major power greedy modules(consuming 39.4%, 16.3%, 13.4%) in a digital baseband subsystem. The power estimation error of the proposed power amplifier(PA) power model is 3.5%(macro cell). The major contribution of this paper is that the proposed models can rapidly estimate energy/power consumption of 4G and the future base stations(such as 5G) in early design stages with well acceptable precision, even without sufficient implementation information.
基金supported in part by the National Natural Science Foundation of China(Nos.61741313,61304223,61673209,61533008)the Jiangsu Six Peak of Talents program(No.KTHY-027)+1 种基金the Aeronautical Science Foundation(No.2016ZA 52009)the Fundamental Research Funds for the Central Universities(Nos.NJ20160026,NS2017015)
文摘Carrier-based aircraft carrier landing is a special kind of tracking control problem and not suitable for classical control methods,which may miss the desired performance or result in overdesign.Therefore,we present an optimal preview control for automatic carrier landing system(ACLS)by using state information of system,as well as future reference information,which can avoid the shortcomings of classical control methods.Since the flight performance of carrier-based aircraft is disturbed by air wake when the aircraft flies near the area of carrier stern,we design a disturbance rejection strategy to ensure that aircraft track the glide path with high precision and robustness.Further,carrier-based aircraft is a complex nonlinear system.However,the nonlinear model of carrier-based aircraft can be linearized at equilibrium landing state and decoupled into the longitudinal model and the lateral model.Therefore,an optimal preview control system is designed.The simulation results of a carrier-based aircraft show that the optimal preview control system can effectively suppress air wake.Tracking accuracy of optimal preview controller is higher than that of the proportional integral differential(PID)control system.
基金supported by the State Grid Science and Technology Project(KJ21-1-56).
文摘Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.
基金supported by the State Grid Science and Technology Project(KJ21-1-56).
文摘The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries.To maximize overall benefits for the investors and operators of base station energy storage,we proposed a bi-level optimization model for the operation of the energy storage,and the planning of 5G base stations considering the sleep mechanism.A multi-base station cooperative system composed of 5G acer stations was considered as the research object,and the outer goal was to maximize the net profit over the complete life cycle of the energy storage.Furthermore,the power and capacity of the energy storage configuration were optimized.The inner goal included the sleep mechanism of the base station,and the optimization of the energy storage charging and discharging strategy,for minimizing the daily electricity expenditure of the 5G base station system.Additionally,genetic algorithm and mixed integer programming were used to solve the bi-level optimization model,analyze the numerical example test comparison of the three types of batteries and the net income of the configuration,and finally verify the validity of the model.Furthermore,the sleep mechanism,the charging and discharging strategy for energy consumption,and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration.
文摘Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.
基金This work was supported by the National Natural Science Foundation of China(No.U1633109)the Fundamental Research Funds for the Central Universities(No.3122016C010).
文摘A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate flight pairs were selected from all international flights arriving at or departing from China in one day according to the requirement of the proposed method.Aircraft performance database Base of Aircraft Data(BADA)was employed in the trajectory computation.By assuming different fuel-saving percentages for the following aircraft,pre-flight plan trajectories of formation flight were optimized.The fuel consumption optimization effect under the influence of different trajectory optimization parameters was also analyzed.The results showed that the higher the fuel savings percentage,the longer the flight distance of formation flight,but the smaller the number of formation combinations that can be realized,which is limited by the aircraft performance.The following aircraft flying along the approximate actual flight trajectory can be benefited as well,and the optimal fuel-saving efficiency is related to the expected fuelsaving efficiency of formation flight.
基金performed within the project ARCWIND-adaptation and implementation of floating wind energy conversion technology for the Atlantic region-which is co-financed by the European Regional Development Fund through the Interreg Atlantic Area Program under contract EAPA 344/2016
文摘The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis and prognosis, and maintenance optimization. Relevant academic research and industrial applications are identified and summarized. The state of art, capabilities,and constraints of condition-based maintenance are analyzed. The presented research demonstrates that the intelligent-based approach has become a promising solution for condition recognition, and an integrated data platform for offshore wind farms is significant to optimize the maintenance activities.
基金supported in part by the National Natural Science Foundations of China(Nos.61304223,61673209,61533008)the Aeronautical Science Foundation(No.2016ZA 52009)the Fundamental Research Funds for the Central Universities(No.NJ20160026)
文摘For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.
基金Supported by the National Natural Science Foundation of China(1117202591116)
文摘The genetic/gradient-based hybrid algorithm is introduced and used in the design studies of aeroelastic optimization of large aircraft wings to attain skin distribution,stiffness distribution and design sensitivity.The program of genetic algorithm is developed by the authors while the gradient-based algorithm borrows from the modified method for feasible direction in MSC/NASTRAN software.In the hybrid algorithm,the genetic algorithm is used to perform global search to avoid to fall into local optima,and then the excellent individuals of every generation optimized by the genetic algorithm are further fine-tuned by the modified method for feasible direction to attain the local optima and hence to get global optima.Moreover,the application effects of hybrid genetic algorithm in aeroelastic multidisciplinary design optimization of large aircraft wing are discussed,which satisfy multiple constraints of strength,displacement,aileron efficiency,and flutter speed.The application results show that the genetic/gradient-based hybrid algorithm is available for aeroelastic optimization of large aircraft wings in initial design phase as well as detailed design phase,and the optimization results are very consistent.Therefore,the design modifications can be decreased using the genetic/gradient-based hybrid algorithm.
文摘Autonomous Underwater Vehicles （AUVs） are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. This framework enhances AUV mission performance by completing the maximum number of highest priority tasks in a limited time through a large-scale waypoint cluttered operating field and ensuring safe deployment during the mission. The proposed combinatorial route-path-planner model takes advantage of the Biogeography- Based Optimization （BBO） algorithm to satisfy the objectives of both higher- and lower-level motion planners and guarantee the maximization of mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios, including cost constraints in time-varying operating fields. To demonstrate the reliability of the proposed model, the performance of each motion planner is separately assessed and statistical analysis is conducted to evaluate the total performance of the entire model. The simulation results indicate the stability of the proposed model and the feasibility of its application to real-time experiments.
基金supported by the Singapore AcRF Tier 1 Grant(RG 19/09)the A*STAR SERC Grant(102 101 0020)
文摘In our former work [Catal. Today 174 （2011） 127], 12 heterogeneous catalysts were screened for CO oxidation, and Au-ZnO/Al2O3 was chosen and optimized in terms of weight loadings of Au and ZnO. The present study follows on to consider the impact of process parameters （catalyst preparation and reaction conditions）, in conjunction with catalyst composition （weight loadings of Au and ZnO, and the total weight of the catalyst）, as the optimization of the process parameters simultaneously optimized the catalyst composition. The optimization target is the reactivity of this important reaction. These factors were first optimized using response surface methodology （RSM） with 25 experiments, to obtain the optimum： 100 mg of 1.0%Au-4.1%ZnO/Al2O3 catalyst with 220℃ calcination and 100℃ reduction. After optimization, the main effects and interactions of these five factors were studied using statistical sensitivity analysis （SA）. Certain observations from SA were verified by reaction mechanism, reactivity test and/or characterization techniques, while others need further investigation.
基金Supported by the National Natural Science Foundation of China(60872065)the Open Foundation of Key Laboratory of Meteorological Disaster of Ministry of Education at Nanjing University of Information Science & Technology(KLME1108)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.
