With the development of electric vehicles(EV), there is a huge demand for electric vehicle charging stations(EVCS). The utilization of renewable energy sources(RES) in EVCS can not only decrease the energy fluctuation...With the development of electric vehicles(EV), there is a huge demand for electric vehicle charging stations(EVCS). The utilization of renewable energy sources(RES) in EVCS can not only decrease the energy fluctuation by participating in peakload reduction of the grid, but also reduce the pollution to the environment by cutting down the use of fossil fuels. In this paper,the optimal planning for grid-connected EVCS with RES is studied by considering EV load uncertainty. Nine scenarios are set based on a different characteristic of EV load to reveal the impact of EV load on net present cost(NPC) and to express the relationship between the optimal capacity and energy flow. Moreover, since electricity price also plays an important role in EVCS planning, an economic comparison between different cases with different electricity prices for peak-valley-flat period is carried out. The results reveal the economic benefits of applying RES in EVCS, and demonstrate that EV load with different characteristics would influence the capacity of each device(PV, battery, converter) in the EVCS optimal planning.展开更多
The genomic scale metabolic networks of the microorganisms can be constructed based on their genome se-quences,functional annotations,and biochemical reactions,reflecting almost all of the metabolic functions.Mathemat...The genomic scale metabolic networks of the microorganisms can be constructed based on their genome se-quences,functional annotations,and biochemical reactions,reflecting almost all of the metabolic functions.Mathematical simulations of metabolic fluxes could make these functions be visualized,thereby providing guidance for rational engineering design and experimental operations.This review summarized recently devel-oped flux simulation algorithms of microbial systems.For the single microbial systems,the optimal planning algorithm has low complexity because there is no interaction between microorganisms,and it can quickly simulate the stable metabolic states through the pseudo-steady hypothesis.Besides,the experimental conditions of single microbial systems are easier to reach or close to the optimal states of simulation,compared with pol-ymicrobial systems.The polymicrobial culture systems could outcompete the single microbial systems as they could relieve metabolic pressure through metabolic division,resource exchange,and complex substrate co-utilization.Besides,they provide varieties of intracellular production environments,which render them the po-tential to achieve efficient bioproduct synthesis.However,due to the quasi-steady hypothesis that restricts the simulation of the dynamic processes of microbial interactions and the algorithm complexity,there are few re-searches on simulation algorithms of polymicrobial metabolic fluxes.Therefore,this review also analyzed and combed the microbial interactions based on the commonly used hypothesis of maximizing growth rates,and studied the strategies of coupling interactions with optimal planning simulations for metabolism.Finally,this review provided new insights into the genomic scale metabolic flux simulations of polymicrobial systems.展开更多
The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution netw...The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source converters.This paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op eration.The characteristics and DC conversion constraints of typical LVDNs are analyzed.In addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC configurations.Moreover,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase unbalance.Simulations are conducted to verify the effectiveness of the proposed optimal planning method.Sim ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.展开更多
A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK ...A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.展开更多
To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of...To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of-freedom parallel platform.Using the platform movement and IMU wearable sensors,two training modes,i.e.,active and passive,are developed to achieve vestibular stimulation.Virtual reality technology is applied to achieve visual stimulation.In the active training mode,the elderly actively exercises to control the posture change of the platform and the switching of the virtual scene.In the passive training mode,the platform movement is combined with the virtual scene to simulate bumpy environments,such as earthquakes,to enhance the human anti-interference ability.To achieve a smooth switching of the scene,continuous speed and acceleration of the platform motion are required in some scenarios,in which a trajectory planning algorithm is applied.This paper describes the application of the trajectory planning algorithm in the balance training mode and the optimization of jerk(differential of acceleration)based on cubic spline planning,which can reduce impact on the joint and enhance stability.展开更多
Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical ...Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.展开更多
The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric v...The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.展开更多
Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and cont...Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and continuous casting （SCC） process. The optimization model combined with parallel-backward inferring algorithm and genetic algorithm is described. To analyze and evaluate the production plans, a simulation model based on cellular automata is presented. And then, the integrated system including the production plan optimization model and the simulation model is introduced to evaluate and adjust the production plan on-line. The test with production data in a steel plant shows that the optimization model demonstrates ability to deal with time uncertainty in production planning and to set up a conflict-free production plan, and the integrated system provides a useful tool for dynamically drawing and adjusting a production plan on-line. The average staying time of the production plan is about 5% shorter than that in a practical process.展开更多
Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the conf...Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.展开更多
This paper presents a novel general method for computing optimal motions of an industrial robot manipulator （AdeptOne XL robot） in the presence of fixed and oscillating obstacles. The optimization model considers th...This paper presents a novel general method for computing optimal motions of an industrial robot manipulator （AdeptOne XL robot） in the presence of fixed and oscillating obstacles. The optimization model considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacle avoidance. The problem has 6 objective functions, 88 variables, and 21 constraints. Two evolutionary algorithms, namely, elitist non-dominated sorting genetic algorithm （NSGA-II） and multi-objective differential evolution （MODE）, have been used for the optimization. Two methods （normalized weighting objective functions and average fitness factor） are used to select the best solution tradeoffs. Two multi-objective performance measures, namely solution spread measure and ratio of non-dominated individuals, are used to evaluate the Pareto optimal fronts. Two multi-objective performance measures, namely, optimizer overhead and algorithm effort, are used to find the computational effort of the optimization algorithm. The trajectories are defined by B-spline functions. The results obtained from NSGA-II and MODE are compared and analyzed.展开更多
Optimal trajectory planning of high-speed trains(HSTs)aims to obtain such speed curves that guarantee safety,punctuality,comfort and energy-saving of the train.In this paper,a new shrinking horizon model predictive co...Optimal trajectory planning of high-speed trains(HSTs)aims to obtain such speed curves that guarantee safety,punctuality,comfort and energy-saving of the train.In this paper,a new shrinking horizon model predictive control(MPC)algorithm is proposed to plan the optimal trajectories of HSTs using real-time traffic information.The nonlinear longitudinal dynamics of HSTs are used to predict the future behaviors of the train and describe variable slopes and variable speed limitations based on real-time traffic information.Then optimal trajectory planning of HSTs is formulated as the shrinking horizon optimal control problem with the consideration of safety,punctuality,comfort and energy consumption.According to the real-time position and running time of the train,the shrinking horizon is updated to ensure the recursive feasibility of the optimization problem.The optimal speed curve of the train is computed by online solving the optimization problem with the Radau Pseudo-spectral method(RPM).Simulation results demonstrate that the proposed method can satisfy the requirements of energy efficiency and punctuality of the train.展开更多
Under Type-Ⅱ progressively hybrid censoring, this paper discusses statistical inference and optimal design on stepstress partially accelerated life test for hybrid system in presence of masked data. It is assumed tha...Under Type-Ⅱ progressively hybrid censoring, this paper discusses statistical inference and optimal design on stepstress partially accelerated life test for hybrid system in presence of masked data. It is assumed that the lifetime of the component in hybrid systems follows independent and identical modified Weibull distributions. The maximum likelihood estimations(MLEs)of the unknown parameters, acceleration factor and reliability indexes are derived by using the Newton-Raphson algorithm. The asymptotic variance-covariance matrix and the approximate confidence intervals are obtained based on normal approximation to the asymptotic distribution of MLEs of model parameters. Moreover,two bootstrap confidence intervals are constructed by using the parametric bootstrap method. The optimal time of changing stress levels is determined under D-optimality and A-optimality criteria.Finally, the Monte Carlo simulation study is carried out to illustrate the proposed procedures.展开更多
Under the demand of strategic air traffic flow management and the concept of trajectory based operations（TBO）,the network-wide 4D flight trajectories planning（N4DFTP） problem has been investigated with the purpose...Under the demand of strategic air traffic flow management and the concept of trajectory based operations（TBO）,the network-wide 4D flight trajectories planning（N4DFTP） problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories（4DTs）（3D position and time） for all the flights in the whole airway network.Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity,an efficient model for strategiclevel conflict management is developed in this paper.Specifically,a bi-objective N4 DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated.In consideration of the large-scale,high-complexity,and multi-objective characteristics of the N4DFTP problem,a multi-objective multi-memetic algorithm（MOMMA） that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented.It is capable of rapidly and effectively allocating 4DTs via rerouting,target time controlling,and flight level changing.Additionally,to balance the ability of exploitation and exploration of the algorithm,a special hybridization scheme is adopted for the integration of local and global search.Empirical studies using real air traffic data in China with different network complexities show that the proposed MOMMA is effective to solve the N4 DFTP problem.The solutions achieved are competitive for elaborate decision support under a TBO environment.展开更多
The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated,and a hybrid optimization strategy based on Gauss pseudospectral method（GPM） and direct shooting method（DSM...The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated,and a hybrid optimization strategy based on Gauss pseudospectral method（GPM） and direct shooting method（DSM） is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions.The results indicate that the method is effective with good robustness.展开更多
Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization r...Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.展开更多
Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulatio...Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.展开更多
Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among member...Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.展开更多
North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewabl...North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewable energies—wind,photovoltaic(PV),and concentrating solar power(CSP)—an optimal planning model is established to minimize construction costs and power curtailment losses.The levelized cost of electricity is used as an index for assessing economic feasibility.In this study,wind and PV,wind/PV/CSP,and transnational interconnection modes are designed for Morocco,Egypt,and Tunisia.The installed capacities of renewable energy power generation are planned through the time sequence production simulation method for each country.The results show that renewable energy combined with power generation,including the CSP mode,can improve reliability of the power supply and reduce the power curtailment rate.The transnational interconnection mode can help realize mutual benefits of renewable energy power,while the apportionment of electricity prices and trading mechanisms are very important and are related to economic feasibility;thus,this mode is important for the future development of renewable energy in North Africa.展开更多
A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a compar...A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing,censoring strategies are frequently used.From this point of view,in the presence of censored data compiled from the most well-known progressively Type-Ⅱ censoring technique,this study examines different parameters of the IGG distribution.From a classical point of view,the likelihood and product of spacing estimation methods are considered.Observed Fisher information and the deltamethod are used to obtain the approximate confidence intervals for any unknown parametric function of the suggestedmodel.In the Bayesian paradigm,the same traditional inferential approaches are used to estimate all unknown subjects.Markov-Chain with Monte-Carlo steps are considered to approximate all Bayes’findings.Extensive numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of accuracy.Further,using several optimality criteria,the optimumprogressive censoring design is suggested.To highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model,we analyze the failure times of twenty mechanical components of a diesel engine.展开更多
基金supported by the International Science and Technology Cooperation Program of China(Grant No.2018YFE0125300)the National Natural Science Foundation of China(Grant No.52061130217)the Science and Technology Project of State Grid Hunan Electric Power Co.,Ltd.(Grant No.5216A2200005)。
文摘With the development of electric vehicles(EV), there is a huge demand for electric vehicle charging stations(EVCS). The utilization of renewable energy sources(RES) in EVCS can not only decrease the energy fluctuation by participating in peakload reduction of the grid, but also reduce the pollution to the environment by cutting down the use of fossil fuels. In this paper,the optimal planning for grid-connected EVCS with RES is studied by considering EV load uncertainty. Nine scenarios are set based on a different characteristic of EV load to reveal the impact of EV load on net present cost(NPC) and to express the relationship between the optimal capacity and energy flow. Moreover, since electricity price also plays an important role in EVCS planning, an economic comparison between different cases with different electricity prices for peak-valley-flat period is carried out. The results reveal the economic benefits of applying RES in EVCS, and demonstrate that EV load with different characteristics would influence the capacity of each device(PV, battery, converter) in the EVCS optimal planning.
基金support from the National Key R&D Program of China(2021YFC2100700)the National Natural Science Foundation of China(21838001,31961133018).
文摘The genomic scale metabolic networks of the microorganisms can be constructed based on their genome se-quences,functional annotations,and biochemical reactions,reflecting almost all of the metabolic functions.Mathematical simulations of metabolic fluxes could make these functions be visualized,thereby providing guidance for rational engineering design and experimental operations.This review summarized recently devel-oped flux simulation algorithms of microbial systems.For the single microbial systems,the optimal planning algorithm has low complexity because there is no interaction between microorganisms,and it can quickly simulate the stable metabolic states through the pseudo-steady hypothesis.Besides,the experimental conditions of single microbial systems are easier to reach or close to the optimal states of simulation,compared with pol-ymicrobial systems.The polymicrobial culture systems could outcompete the single microbial systems as they could relieve metabolic pressure through metabolic division,resource exchange,and complex substrate co-utilization.Besides,they provide varieties of intracellular production environments,which render them the po-tential to achieve efficient bioproduct synthesis.However,due to the quasi-steady hypothesis that restricts the simulation of the dynamic processes of microbial interactions and the algorithm complexity,there are few re-searches on simulation algorithms of polymicrobial metabolic fluxes.Therefore,this review also analyzed and combed the microbial interactions based on the commonly used hypothesis of maximizing growth rates,and studied the strategies of coupling interactions with optimal planning simulations for metabolism.Finally,this review provided new insights into the genomic scale metabolic flux simulations of polymicrobial systems.
基金supported by the National Key Research and Development Program of China(No.2019YFE0118400).
文摘The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source converters.This paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op eration.The characteristics and DC conversion constraints of typical LVDNs are analyzed.In addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC configurations.Moreover,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase unbalance.Simulations are conducted to verify the effectiveness of the proposed optimal planning method.Sim ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.
文摘A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
基金Supported by National Key R&D Program of China(Grant No.2019YFB1311404)。
文摘To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of-freedom parallel platform.Using the platform movement and IMU wearable sensors,two training modes,i.e.,active and passive,are developed to achieve vestibular stimulation.Virtual reality technology is applied to achieve visual stimulation.In the active training mode,the elderly actively exercises to control the posture change of the platform and the switching of the virtual scene.In the passive training mode,the platform movement is combined with the virtual scene to simulate bumpy environments,such as earthquakes,to enhance the human anti-interference ability.To achieve a smooth switching of the scene,continuous speed and acceleration of the platform motion are required in some scenarios,in which a trajectory planning algorithm is applied.This paper describes the application of the trajectory planning algorithm in the balance training mode and the optimization of jerk(differential of acceleration)based on cubic spline planning,which can reduce impact on the joint and enhance stability.
文摘Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.
基金the National Social Science Foundation of China(No.18AJL014)。
文摘The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.
基金Item Sponsored by National High-Tech Research and Development Plan of China(2007AA04Z161)
文摘Aiming at the limitations of the traditional mathematical model for production planning, a novel optimization model is proposed to improve the efficiency and performance for production planning in steelmaking and continuous casting （SCC） process. The optimization model combined with parallel-backward inferring algorithm and genetic algorithm is described. To analyze and evaluate the production plans, a simulation model based on cellular automata is presented. And then, the integrated system including the production plan optimization model and the simulation model is introduced to evaluate and adjust the production plan on-line. The test with production data in a steel plant shows that the optimization model demonstrates ability to deal with time uncertainty in production planning and to set up a conflict-free production plan, and the integrated system provides a useful tool for dynamically drawing and adjusting a production plan on-line. The average staying time of the production plan is about 5% shorter than that in a practical process.
基金This work was partially supported by National Key R&D Program of China(2019YFB1312400)Shenzhen Key Laboratory of Robotics Perception and Intelligence(ZDSYS20200810171800001)+1 种基金Hong Kong RGC GRF(14200618)Hong Kong RGC CRF(C4063-18G).
文摘Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.
文摘This paper presents a novel general method for computing optimal motions of an industrial robot manipulator （AdeptOne XL robot） in the presence of fixed and oscillating obstacles. The optimization model considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacle avoidance. The problem has 6 objective functions, 88 variables, and 21 constraints. Two evolutionary algorithms, namely, elitist non-dominated sorting genetic algorithm （NSGA-II） and multi-objective differential evolution （MODE）, have been used for the optimization. Two methods （normalized weighting objective functions and average fitness factor） are used to select the best solution tradeoffs. Two multi-objective performance measures, namely solution spread measure and ratio of non-dominated individuals, are used to evaluate the Pareto optimal fronts. Two multi-objective performance measures, namely, optimizer overhead and algorithm effort, are used to find the computational effort of the optimization algorithm. The trajectories are defined by B-spline functions. The results obtained from NSGA-II and MODE are compared and analyzed.
基金supported by the National Natural Science Foundation of China(No.61773345)the Zhejang Provincial Natural Science Foundation(No.LR17F030004).
文摘Optimal trajectory planning of high-speed trains(HSTs)aims to obtain such speed curves that guarantee safety,punctuality,comfort and energy-saving of the train.In this paper,a new shrinking horizon model predictive control(MPC)algorithm is proposed to plan the optimal trajectories of HSTs using real-time traffic information.The nonlinear longitudinal dynamics of HSTs are used to predict the future behaviors of the train and describe variable slopes and variable speed limitations based on real-time traffic information.Then optimal trajectory planning of HSTs is formulated as the shrinking horizon optimal control problem with the consideration of safety,punctuality,comfort and energy consumption.According to the real-time position and running time of the train,the shrinking horizon is updated to ensure the recursive feasibility of the optimization problem.The optimal speed curve of the train is computed by online solving the optimization problem with the Radau Pseudo-spectral method(RPM).Simulation results demonstrate that the proposed method can satisfy the requirements of energy efficiency and punctuality of the train.
基金supported by the National Natural Science Foundation of China(71401134 71571144+1 种基金 71171164)the Program of International Cooperation and Exchanges in Science and Technology Funded by Shaanxi Province(2016KW-033)
文摘Under Type-Ⅱ progressively hybrid censoring, this paper discusses statistical inference and optimal design on stepstress partially accelerated life test for hybrid system in presence of masked data. It is assumed that the lifetime of the component in hybrid systems follows independent and identical modified Weibull distributions. The maximum likelihood estimations(MLEs)of the unknown parameters, acceleration factor and reliability indexes are derived by using the Newton-Raphson algorithm. The asymptotic variance-covariance matrix and the approximate confidence intervals are obtained based on normal approximation to the asymptotic distribution of MLEs of model parameters. Moreover,two bootstrap confidence intervals are constructed by using the parametric bootstrap method. The optimal time of changing stress levels is determined under D-optimality and A-optimality criteria.Finally, the Monte Carlo simulation study is carried out to illustrate the proposed procedures.
基金co-supported by the National Science Foundation for Young Scientists of China(No.61401011)the National Key Technologies R&D Program of China(No.2015BAG15B01)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.61521091)
文摘Under the demand of strategic air traffic flow management and the concept of trajectory based operations（TBO）,the network-wide 4D flight trajectories planning（N4DFTP） problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories（4DTs）（3D position and time） for all the flights in the whole airway network.Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity,an efficient model for strategiclevel conflict management is developed in this paper.Specifically,a bi-objective N4 DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated.In consideration of the large-scale,high-complexity,and multi-objective characteristics of the N4DFTP problem,a multi-objective multi-memetic algorithm（MOMMA） that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented.It is capable of rapidly and effectively allocating 4DTs via rerouting,target time controlling,and flight level changing.Additionally,to balance the ability of exploitation and exploration of the algorithm,a special hybridization scheme is adopted for the integration of local and global search.Empirical studies using real air traffic data in China with different network complexities show that the proposed MOMMA is effective to solve the N4 DFTP problem.The solutions achieved are competitive for elaborate decision support under a TBO environment.
基金supported by the National Natural Science Foundation of China (11472058)
文摘The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated,and a hybrid optimization strategy based on Gauss pseudospectral method（GPM） and direct shooting method（DSM） is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions.The results indicate that the method is effective with good robustness.
文摘Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.
基金Science and Technology Projects of State Grid Corporation of China(No.SGGSKY00FJJS1800140)。
文摘Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.
基金supported by the National Social Science Foundation of China in 2012 under Grant No. 11GJ003-074the Science Foundation of Aeronautics of China under Grant No. 20085584010
文摘Cooperative path dynamic planning of a UCAV （unmanned combat air vehicle） team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.
基金Supported by the Science and Technology Foundation of SGCC(Large-scale development and utilization mode of solar energy in North Africa under the condition of transcontinental grid interconnection:NY71-18-004)the Science and Technology Foundation of GEI(Research on Large-scale Solar Energy Development in West-Asia and North-Africa:NYN11201805034)
文摘North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewable energies—wind,photovoltaic(PV),and concentrating solar power(CSP)—an optimal planning model is established to minimize construction costs and power curtailment losses.The levelized cost of electricity is used as an index for assessing economic feasibility.In this study,wind and PV,wind/PV/CSP,and transnational interconnection modes are designed for Morocco,Egypt,and Tunisia.The installed capacities of renewable energy power generation are planned through the time sequence production simulation method for each country.The results show that renewable energy combined with power generation,including the CSP mode,can improve reliability of the power supply and reduce the power curtailment rate.The transnational interconnection mode can help realize mutual benefits of renewable energy power,while the apportionment of electricity prices and trading mechanisms are very important and are related to economic feasibility;thus,this mode is important for the future development of renewable energy in North Africa.
基金funded by the Deanship of Scientific Research and Libraries,Princess Nourah bint Abdulrahman University,through the Program of Research Project Funding after Publication,Grant No.(RPFAP-34-1445).
文摘A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing,censoring strategies are frequently used.From this point of view,in the presence of censored data compiled from the most well-known progressively Type-Ⅱ censoring technique,this study examines different parameters of the IGG distribution.From a classical point of view,the likelihood and product of spacing estimation methods are considered.Observed Fisher information and the deltamethod are used to obtain the approximate confidence intervals for any unknown parametric function of the suggestedmodel.In the Bayesian paradigm,the same traditional inferential approaches are used to estimate all unknown subjects.Markov-Chain with Monte-Carlo steps are considered to approximate all Bayes’findings.Extensive numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of accuracy.Further,using several optimality criteria,the optimumprogressive censoring design is suggested.To highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model,we analyze the failure times of twenty mechanical components of a diesel engine.
