This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss r...This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.展开更多
The distribution networks sometimes suffer from excessive losses and voltage violations in densely populated areas. The aim of the present study is to improve the performance of a distribution network by successively ...The distribution networks sometimes suffer from excessive losses and voltage violations in densely populated areas. The aim of the present study is to improve the performance of a distribution network by successively applying mono-capacitor positioning, multiple positioning and reconfiguration processes using GA-based algorithms implemented in a Matlab environment. From the diagnostic study of this network, it was observed that a minimum voltage of 0.90 pu induces a voltage deviation of 5.26%, followed by active and reactive losses of 425.08 kW and 435.09 kVAR, respectively. Single placement with the NSGAII resulted in the placement of a 3000 kVAR capacitor at node 128, which proved to be the invariably neuralgic point. Multiple placements resulted in a 21.55% reduction in losses and a 0.74% regression in voltage profile performance. After topology optimization, the loss profile improved by 65.08% and the voltage profile improved by 1.05%. Genetic algorithms are efficient and effective tools for improving the performance of distribution networks, whose degradation is often dynamic due to the natural variability of loads.展开更多
Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quali...Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.展开更多
This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a n...This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution system.The goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system constraints.The optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.展开更多
Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capa...Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.展开更多
Future aerospace vehicles （ASV） are designed to fly in both inner and extra atmospheric fields, which requires autonomous adaptability to the uncertainties emanated from abrupt faults and continuously time-varying e...Future aerospace vehicles （ASV） are designed to fly in both inner and extra atmospheric fields, which requires autonomous adaptability to the uncertainties emanated from abrupt faults and continuously time-varying environments. An autonomous control reconfiguration scheme is presented for ASV to deal with the uncertainties on the base of control effectiveness estimation. The on-line estimation methods for the time-varying control effectiveness of linear control system are investigated. Some sufficient conditions for the estimable system are given for different cases. There are proposed corresponding on-line estimation algorithms which are proved to be convergent and robust to noise using the least-square-based methods. On the ground of fuzzy logic and linear programming, the control allocation algorithms, which are able to implement the autonomous control reconfiguration through the redundant actuators, are put forward. Finally, an integrated system is developed to verify the scheme and algorithms by way of numerical simulation and analysis.展开更多
Abstract： With a determinate danger zone and evacuation demand caused by an emergency, an optimization method for the evacuation zone with network reconfiguration based on dynamic simulation is proposed. The method c...Abstract： With a determinate danger zone and evacuation demand caused by an emergency, an optimization method for the evacuation zone with network reconfiguration based on dynamic simulation is proposed. The method contains three modules. First, the network in the evacuation zone is optimized by a model with the integrated strategy of lane reversal and intersection conflict elimination. Secondly, the dynamic evacuation simulation model based on the cell transmission model is applied to simulate the dynamic propagation process of evacuated vehicles in the network in the evacuation zone. The evacuation time for all evacuated vehicles leaving the danger zone is obtained and the setting of the current evacuation zone is fed back. Thirdly, the arrival distributions of evacuated vehicles at critical intersections of the evacuation zone are also obtained to estimate the delay at critical intersection to determine whether the intersection should be taken as the critical intersection in the next iteration. The evacuation zone is expanded gradually through iteration, and the reasonable evacuation zone and the optimal evacuation network is confirmed. Based on the survey of the parking lot and urban street network around Nanjing Olympic Sports Center, the models and the iterative algorithm were applied to obtain the optimal plan of the evacuation zone with network reconfiguration in an evacuation situation to verify the validity of the proposed method.展开更多
This paper presents a genetic programming based reconfiguration planner for metamorphic modular robots. Initially used for evolving computer programs that can solve simple problems, genetic programming （GP） has been...This paper presents a genetic programming based reconfiguration planner for metamorphic modular robots. Initially used for evolving computer programs that can solve simple problems, genetic programming （GP） has been recently used to handle various kinds of problems in the area of complex systems. This paper details how genetic programming can be used as an automatic programming tool for handling reconfiguration-planning problem. To do so, the GP evolves sequences of basic operations which are required for transforming the robot＇s geometric structure from its initial configuration into the target one while the total number of modules and their connectedness are preserved. The proposed planner is intended for both Crystalline and TeleCube modules which are achieved by cubical compressible units. The target pattern of the modular robot is expressed in quantitative terms of morphogens diffused on the environment. Our work presents a solution for self recontlguration problem with restricted and unrestricted free space available to the robot during reconfiguration, The planner outputs a near optimal explicit sequence of low-level actions that allows modules to move relative to each other in order to form the desired shape.展开更多
Aimed at the complex flight control system of a fighter,a kind of robust adaptive control methods using multiple models is presented to make the control system track the given signal under different working conditions...Aimed at the complex flight control system of a fighter,a kind of robust adaptive control methods using multiple models is presented to make the control system track the given signal under different working conditions and to reconfigure the control law for some structural failures. Firstly,the multiple-model control structure is formed by several linear models and one fuzzy model. In the fuzzy logic way,weights of the multiple-model adaptive controller are obtained. Then,a dynamic structure adaptive neural network is introduced to stabilize the whole system and eliminate the influence caused by the frequent switching. Simulation results show that the control method is effective by demonstrating the normal flight process and the control simulation with failures.展开更多
An efficient algorithm ESA combining evolution strategies(ES) with simulated annealing(SA) is proposed in this paper. We first use ES to choose an initial temperature, then use a modified SA to find a global optimum f...An efficient algorithm ESA combining evolution strategies(ES) with simulated annealing(SA) is proposed in this paper. We first use ES to choose an initial temperature, then use a modified SA to find a global optimum for the problem. An efficient load flow method and a heuristic criterion for determining the temperature lowering scheme are employed in order to speed up the computation. The solution algorithm has been tested on a distribution system with very promising results.展开更多
This paper develops a novel optimization method oriented to the resilience of multiple Unmanned Aerial Vehicle(multi-UAV)formations to achieve rapid and accurate reconfiguration under random attacks.First,a resilience...This paper develops a novel optimization method oriented to the resilience of multiple Unmanned Aerial Vehicle(multi-UAV)formations to achieve rapid and accurate reconfiguration under random attacks.First,a resilience metric is applied to reflect the effect and rapidity of multi-UAV formation resisting random attacks.Second,an optimization model based on a parameter optimization problem to maximize the system resilience is established.Third,an Adaptive Learning-based Pigeon-Inspired Optimization(ALPIO)algorithm is designed to optimize the resilience value.Finally,typical formation topologies with six UAVs are investigated as a case study to verify the proposed approach.The experimental results indicate that the proposed scheme can achieve resilience optimization for a multi-UAV formation reconfiguration by increasing the system resilience values to 97.53%and 81.4%after random attacks.展开更多
Reconfiguration of formation flying around a halo orbit of the Sun-Earth restricted three body system is investigated with impulse maneuvers. For a short time reconfiguration, the two-impulse maneuver is investigated ...Reconfiguration of formation flying around a halo orbit of the Sun-Earth restricted three body system is investigated with impulse maneuvers. For a short time reconfiguration, the two-impulse maneuver is investigated with both analytical and numerical methods and the Beginning-Ending （BE） method is proven to be an energy-optimal one of all two-impulse （TI） reconfigurations, and the energy consumption of BE is independent of the position of the chief spacecraft, and decreases with the reconfiguration time. Then, genetic algorithm is adopted to optimize the energy consumption. The results show that the optimal energy increases with radius difference between the initial and final orbits, and decreases with the reconfiguration time.展开更多
Multiple UAVs are usually deployed to provide robustness through redundancy and to accomplish surveillance,search,attack and rescue missions.Formation reconfiguration was inevitable during the flight when the mission ...Multiple UAVs are usually deployed to provide robustness through redundancy and to accomplish surveillance,search,attack and rescue missions.Formation reconfiguration was inevitable during the flight when the mission was adjusted or the environment varied.Taking the typical formation reconfiguration from a triangular penetrating formation to a circular tracking formation for example,a path planning method based on Dubins trajectory and particle swarm optimization(PSO)algorithm is presented in this paper.The mathematic model of multiple UAVs formation reconfiguration was built firstly.According to the kinematic model of aerial vehicles,a process of dimensionality reduction was carried out to simplify the model based on Dubins trajectory.The PSO algorithm was adopted to resolve the optimization problem of formation reconfiguration path planning.Finally,the simulation and vehicles flight experiment are executed.Results show that the path planning method based on the Dubins trajectory and the PSO algorithm can generate feasible paths for vehicles on time,to guarantee the rapidity and effectiveness of formation reconfigurations.Furthermore,from the simulation results,the method is universal and could be extended easily to the path planning problem for different kinds of formation reconfigurations.展开更多
In order to accommodate the variety of algorithms with different performance in specific application and improve power efficiency,reconfigurable architecture has become an effective methodology in academia and industr...In order to accommodate the variety of algorithms with different performance in specific application and improve power efficiency,reconfigurable architecture has become an effective methodology in academia and industry.However,existing architectures suffer from performance bottleneck due to slow updating of contexts and inadequate flexibility.This paper presents an H-tree based reconfiguration mechanism(HRM)with Huffman-coding-like and mask addressing method in a homogeneous processing element(PE)array,which supports both programmable and data-driven modes.The proposed HRM can transfer reconfiguration instructions/contexts to a particular PE or associated PEs simultaneously in one clock cycle in unicast,multicast and broadcast mode,and shut down the unnecessary PE/PEs according to the current configuration.To verify the correctness and efficiency,we implement it in RTL synthesis and FPGA prototype.Compared to prior works,the experiment results show that the HRM has improved the work frequency by an average of 23.4%,increased the updating speed by 2×,and reduced the area by 36.9%;HRM can also power off the unnecessary PEs which reduced 51%of dynamic power dissipation in certain application configuration.Furthermore,in the data-driven mode,the system frequency can reach 214 MHz,which is 1.68×higher compared with the programmable mode.展开更多
Creep mechanism was well-known to be mainly dominated by the dislocation sliding and climbing during creep deformation. Here we study the creep deformation of an Al-Cu-Li alloy with the assistance of electropulsing an...Creep mechanism was well-known to be mainly dominated by the dislocation sliding and climbing during creep deformation. Here we study the creep deformation of an Al-Cu-Li alloy with the assistance of electropulsing and subsequent microstructural observations. We find that creep strain increased drastically under electropulsing and was almost twelve times as much as that of the non-pulsed sample. Microstructural observations confirmed that dislocation reconfiguration happens via electropulsing, namely helical dislocations being opened rapidly. This opened dislocation structure can possess a much higher mobility than the initial helical dislocation, which mostly responsible for the greatly increased creep strain. Our results revealed a new mechanism accountable for the distinctly electroplastic creep deformation.展开更多
Electric power is widely used as the main energy source of ship integrated power system(SIPS), which contains power network and electric power network. SIPS network reconfiguration is a non-linear large-scale problem....Electric power is widely used as the main energy source of ship integrated power system(SIPS), which contains power network and electric power network. SIPS network reconfiguration is a non-linear large-scale problem. The reconfiguration solution influences the safety and stable operation of the power system. According to the operational characteristics of SIPS, a simplified model of power network and a mathematical model for network reconfiguration are established. Based on these models, a multi-agent and ant colony optimization(MAACO) is proposed to solve the problem of network reconfiguration. The simulations are carried out to demonstrate that the optimization method can reconstruct the integrated power system network accurately and efficiently.展开更多
Fault reconfiguration of shipboard power system is viewed as a typical nonlinear and multi-objective combinatorial optimization problem. A comprehensive reconfiguration model is presented in this paper, in which the r...Fault reconfiguration of shipboard power system is viewed as a typical nonlinear and multi-objective combinatorial optimization problem. A comprehensive reconfiguration model is presented in this paper, in which the restored loads, switch frequency and generator efficiency are taken into account. In this model, analytic hierarchy process(AHP) is proposed to determine the coefficients of these objective functions. Meanwhile, a quantum differential evolution algorithm with triple quantum bit code is proposed. This algorithm aiming at the characteristics of shipboard power system is different from the normal quantum bit representation. The individual polymorphic expression is realized, and the convergence performance can be further enhanced in combination with the global parallel search capacity of differential evolution algorithm and the superposition properties of quantum theory. The local optimum can be avoided by dynamic rotation gate. The validity of algorithm and model is verified by the simulation examples.展开更多
With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the o...With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the optimal configuration of improving economy of the system,and then identifying the important nodes.In this strategy,the objectives increase the node importance degree and decrease the active power loss subjected to operational constraints.A compound objective function with weight coefficients is formulated to balance the conflict of the objectives.Then a novel quantum particle swarm optimization based on loop switches hierarchical encoded was employed to address the compound objective reconfiguration problem.Its main contribution is the presentation of the hierarchical encoded scheme which is used to generate the population swarm particles of representing only radial connected solutions.Because the candidate solutions are feasible,the search efficiency would improve dramatically during the optimization process without tedious topology verification.To validate the proposed strategy,simulations are carried out on the test systems.The results are compared with other techniques in order to evaluate the performance of the proposed method.展开更多
Reconfigurability of the electrical network in a shipboard power system （SPS） after its failure is central to the restoration of power supply and improves survivability of an SPS. The navigational process creates a ...Reconfigurability of the electrical network in a shipboard power system （SPS） after its failure is central to the restoration of power supply and improves survivability of an SPS. The navigational process creates a sequence of different operating conditions. The priority of some loads differs in changing operating conditions. After analyzing characteristics of typical SPS, a model was developed used a grade III switchboard and an environmental prioritizing agent （EPA） algorithm. This algorithm was chosen as it is logically and physically decentralized as well as multi-agent oriented. The EPA algorithm was used to decide on the dynamic load priority, then it selected the means to best meet the maximum power supply load. The simulation results showed that higher priority loads were the first to be restored. The system satisfied all necessary constraints, demonstrating the effectiveness and validity of the proposed method.展开更多
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.
文摘The distribution networks sometimes suffer from excessive losses and voltage violations in densely populated areas. The aim of the present study is to improve the performance of a distribution network by successively applying mono-capacitor positioning, multiple positioning and reconfiguration processes using GA-based algorithms implemented in a Matlab environment. From the diagnostic study of this network, it was observed that a minimum voltage of 0.90 pu induces a voltage deviation of 5.26%, followed by active and reactive losses of 425.08 kW and 435.09 kVAR, respectively. Single placement with the NSGAII resulted in the placement of a 3000 kVAR capacitor at node 128, which proved to be the invariably neuralgic point. Multiple placements resulted in a 21.55% reduction in losses and a 0.74% regression in voltage profile performance. After topology optimization, the loss profile improved by 65.08% and the voltage profile improved by 1.05%. Genetic algorithms are efficient and effective tools for improving the performance of distribution networks, whose degradation is often dynamic due to the natural variability of loads.
文摘Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.
基金supported in part by the European Regional Development Fund under Grant KK.01.1.1.01.0009(DATACROSS).
文摘This paper deals with reduction of losses in electric power distribution system through a dynamic reconfiguration case study of a grid in the city of Mostar,Bosnia and Herzegovina.The proposed solution is based on a nonlinear model predictive control algorithm which determines the optimal switching operations of the distribution system.The goal of the control algorithm is to find the optimal radial network topology which minimizes cumulative active power losses and maximizes voltages across the network while simultaneously satisfying all system constraints.The optimization results are validated through multiple simulations(using real power demand data collected for a few characteristic days during winter and summer)which demonstrate the efficiency and usefulness of the developed control algorithm in reducing the grid losses by up to 14%.
基金the financial support from the National Key Research and Development Program of China(No.2023YFB3907001)the National Natural Science Foundation of China(Nos.U2233217,62371029)the UK Engineering and Physical Sciences Research Council(EPSRC),China(Nos.EP/M026981/1,EP/T021063/1 and EP/T024917/)。
文摘Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.
基金National Natural Science Foundation of China (90205011, 60674103)
文摘Future aerospace vehicles （ASV） are designed to fly in both inner and extra atmospheric fields, which requires autonomous adaptability to the uncertainties emanated from abrupt faults and continuously time-varying environments. An autonomous control reconfiguration scheme is presented for ASV to deal with the uncertainties on the base of control effectiveness estimation. The on-line estimation methods for the time-varying control effectiveness of linear control system are investigated. Some sufficient conditions for the estimable system are given for different cases. There are proposed corresponding on-line estimation algorithms which are proved to be convergent and robust to noise using the least-square-based methods. On the ground of fuzzy logic and linear programming, the control allocation algorithms, which are able to implement the autonomous control reconfiguration through the redundant actuators, are put forward. Finally, an integrated system is developed to verify the scheme and algorithms by way of numerical simulation and analysis.
基金The National Natural Science Foundation of China(No.51408190)
文摘Abstract： With a determinate danger zone and evacuation demand caused by an emergency, an optimization method for the evacuation zone with network reconfiguration based on dynamic simulation is proposed. The method contains three modules. First, the network in the evacuation zone is optimized by a model with the integrated strategy of lane reversal and intersection conflict elimination. Secondly, the dynamic evacuation simulation model based on the cell transmission model is applied to simulate the dynamic propagation process of evacuated vehicles in the network in the evacuation zone. The evacuation time for all evacuated vehicles leaving the danger zone is obtained and the setting of the current evacuation zone is fed back. Thirdly, the arrival distributions of evacuated vehicles at critical intersections of the evacuation zone are also obtained to estimate the delay at critical intersection to determine whether the intersection should be taken as the critical intersection in the next iteration. The evacuation zone is expanded gradually through iteration, and the reasonable evacuation zone and the optimal evacuation network is confirmed. Based on the survey of the parking lot and urban street network around Nanjing Olympic Sports Center, the models and the iterative algorithm were applied to obtain the optimal plan of the evacuation zone with network reconfiguration in an evacuation situation to verify the validity of the proposed method.
文摘This paper presents a genetic programming based reconfiguration planner for metamorphic modular robots. Initially used for evolving computer programs that can solve simple problems, genetic programming （GP） has been recently used to handle various kinds of problems in the area of complex systems. This paper details how genetic programming can be used as an automatic programming tool for handling reconfiguration-planning problem. To do so, the GP evolves sequences of basic operations which are required for transforming the robot＇s geometric structure from its initial configuration into the target one while the total number of modules and their connectedness are preserved. The proposed planner is intended for both Crystalline and TeleCube modules which are achieved by cubical compressible units. The target pattern of the modular robot is expressed in quantitative terms of morphogens diffused on the environment. Our work presents a solution for self recontlguration problem with restricted and unrestricted free space available to the robot during reconfiguration, The planner outputs a near optimal explicit sequence of low-level actions that allows modules to move relative to each other in order to form the desired shape.
基金Supported by the National Natural Science Foundation of China (60234010)the Aviation ScienceFoundation of China (05E52031)~~
文摘Aimed at the complex flight control system of a fighter,a kind of robust adaptive control methods using multiple models is presented to make the control system track the given signal under different working conditions and to reconfigure the control law for some structural failures. Firstly,the multiple-model control structure is formed by several linear models and one fuzzy model. In the fuzzy logic way,weights of the multiple-model adaptive controller are obtained. Then,a dynamic structure adaptive neural network is introduced to stabilize the whole system and eliminate the influence caused by the frequent switching. Simulation results show that the control method is effective by demonstrating the normal flight process and the control simulation with failures.
文摘An efficient algorithm ESA combining evolution strategies(ES) with simulated annealing(SA) is proposed in this paper. We first use ES to choose an initial temperature, then use a modified SA to find a global optimum for the problem. An efficient load flow method and a heuristic criterion for determining the temperature lowering scheme are employed in order to speed up the computation. The solution algorithm has been tested on a distribution system with very promising results.
基金supported by the National Defense Pre-Research Foundation of China(No.61400020109).
文摘This paper develops a novel optimization method oriented to the resilience of multiple Unmanned Aerial Vehicle(multi-UAV)formations to achieve rapid and accurate reconfiguration under random attacks.First,a resilience metric is applied to reflect the effect and rapidity of multi-UAV formation resisting random attacks.Second,an optimization model based on a parameter optimization problem to maximize the system resilience is established.Third,an Adaptive Learning-based Pigeon-Inspired Optimization(ALPIO)algorithm is designed to optimize the resilience value.Finally,typical formation topologies with six UAVs are investigated as a case study to verify the proposed approach.The experimental results indicate that the proposed scheme can achieve resilience optimization for a multi-UAV formation reconfiguration by increasing the system resilience values to 97.53%and 81.4%after random attacks.
基金The project supported by the National Natural Science Foundation of China(10672084 and 10672084)The Special Science Foundation of the Doctoral Discipline of the Minstry of Education of China(20060003097)
文摘Reconfiguration of formation flying around a halo orbit of the Sun-Earth restricted three body system is investigated with impulse maneuvers. For a short time reconfiguration, the two-impulse maneuver is investigated with both analytical and numerical methods and the Beginning-Ending （BE） method is proven to be an energy-optimal one of all two-impulse （TI） reconfigurations, and the energy consumption of BE is independent of the position of the chief spacecraft, and decreases with the reconfiguration time. Then, genetic algorithm is adopted to optimize the energy consumption. The results show that the optimal energy increases with radius difference between the initial and final orbits, and decreases with the reconfiguration time.
基金Project (61703414) supported by the National Natural Science Foundation of ChinaProject (3101047) supported by the Defense Science and Technology Foundation of China+1 种基金Project (2017JJ3366) supported by the Natural Science Foundation of Hunan ChinaProject (2015M582881) supported by the China Postdoctoral Science Foundation
文摘Multiple UAVs are usually deployed to provide robustness through redundancy and to accomplish surveillance,search,attack and rescue missions.Formation reconfiguration was inevitable during the flight when the mission was adjusted or the environment varied.Taking the typical formation reconfiguration from a triangular penetrating formation to a circular tracking formation for example,a path planning method based on Dubins trajectory and particle swarm optimization(PSO)algorithm is presented in this paper.The mathematic model of multiple UAVs formation reconfiguration was built firstly.According to the kinematic model of aerial vehicles,a process of dimensionality reduction was carried out to simplify the model based on Dubins trajectory.The PSO algorithm was adopted to resolve the optimization problem of formation reconfiguration path planning.Finally,the simulation and vehicles flight experiment are executed.Results show that the path planning method based on the Dubins trajectory and the PSO algorithm can generate feasible paths for vehicles on time,to guarantee the rapidity and effectiveness of formation reconfigurations.Furthermore,from the simulation results,the method is universal and could be extended easily to the path planning problem for different kinds of formation reconfigurations.
基金supported by the National Natural Science Foundation of China (Nos. 61834005, 61602377, 61772417, 61802304, 61874087)the Shaanxi International Science and Technology Cooperation Program No. 2018KW-006+1 种基金Shaanxi Provincial Key R&D Plan under Grant No. 2017GY-060Shaanxi Province Co-ordination Innovation Project of Science and Technology under Grant No. 2016KTZDGY02-04-02
文摘In order to accommodate the variety of algorithms with different performance in specific application and improve power efficiency,reconfigurable architecture has become an effective methodology in academia and industry.However,existing architectures suffer from performance bottleneck due to slow updating of contexts and inadequate flexibility.This paper presents an H-tree based reconfiguration mechanism(HRM)with Huffman-coding-like and mask addressing method in a homogeneous processing element(PE)array,which supports both programmable and data-driven modes.The proposed HRM can transfer reconfiguration instructions/contexts to a particular PE or associated PEs simultaneously in one clock cycle in unicast,multicast and broadcast mode,and shut down the unnecessary PE/PEs according to the current configuration.To verify the correctness and efficiency,we implement it in RTL synthesis and FPGA prototype.Compared to prior works,the experiment results show that the HRM has improved the work frequency by an average of 23.4%,increased the updating speed by 2×,and reduced the area by 36.9%;HRM can also power off the unnecessary PEs which reduced 51%of dynamic power dissipation in certain application configuration.Furthermore,in the data-driven mode,the system frequency can reach 214 MHz,which is 1.68×higher compared with the programmable mode.
基金financially supported by the Science and Technology Innovation Program of Hunan Province (No.2020RC4001)the National Natural Science Foundation of China (Nos.51905551,52175373,52005516,)+1 种基金the Free Exploration Project of State Key Laboratory of High-performance Complex Manufacturing (No.ZZYJKT2021-03)the financial support from China Postdoctoral Science Foundation (No.2021M693552)。
文摘Creep mechanism was well-known to be mainly dominated by the dislocation sliding and climbing during creep deformation. Here we study the creep deformation of an Al-Cu-Li alloy with the assistance of electropulsing and subsequent microstructural observations. We find that creep strain increased drastically under electropulsing and was almost twelve times as much as that of the non-pulsed sample. Microstructural observations confirmed that dislocation reconfiguration happens via electropulsing, namely helical dislocations being opened rapidly. This opened dislocation structure can possess a much higher mobility than the initial helical dislocation, which mostly responsible for the greatly increased creep strain. Our results revealed a new mechanism accountable for the distinctly electroplastic creep deformation.
基金supported by the National Natural Science Foundation of China (4177402141974005)。
文摘Electric power is widely used as the main energy source of ship integrated power system(SIPS), which contains power network and electric power network. SIPS network reconfiguration is a non-linear large-scale problem. The reconfiguration solution influences the safety and stable operation of the power system. According to the operational characteristics of SIPS, a simplified model of power network and a mathematical model for network reconfiguration are established. Based on these models, a multi-agent and ant colony optimization(MAACO) is proposed to solve the problem of network reconfiguration. The simulations are carried out to demonstrate that the optimization method can reconstruct the integrated power system network accurately and efficiently.
基金the National Natural Science Foundation of China(No.51175321)the Innovation Program of Shanghai Municipal Education Commission(No.12ZZ158)
文摘Fault reconfiguration of shipboard power system is viewed as a typical nonlinear and multi-objective combinatorial optimization problem. A comprehensive reconfiguration model is presented in this paper, in which the restored loads, switch frequency and generator efficiency are taken into account. In this model, analytic hierarchy process(AHP) is proposed to determine the coefficients of these objective functions. Meanwhile, a quantum differential evolution algorithm with triple quantum bit code is proposed. This algorithm aiming at the characteristics of shipboard power system is different from the normal quantum bit representation. The individual polymorphic expression is realized, and the convergence performance can be further enhanced in combination with the global parallel search capacity of differential evolution algorithm and the superposition properties of quantum theory. The local optimum can be avoided by dynamic rotation gate. The validity of algorithm and model is verified by the simulation examples.
基金Project(61102039)supported by the National Natural Science Foundation of ChinaProject(2014AA052600)supported by National Hi-tech Research and Development Plan,China
文摘With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the optimal configuration of improving economy of the system,and then identifying the important nodes.In this strategy,the objectives increase the node importance degree and decrease the active power loss subjected to operational constraints.A compound objective function with weight coefficients is formulated to balance the conflict of the objectives.Then a novel quantum particle swarm optimization based on loop switches hierarchical encoded was employed to address the compound objective reconfiguration problem.Its main contribution is the presentation of the hierarchical encoded scheme which is used to generate the population swarm particles of representing only radial connected solutions.Because the candidate solutions are feasible,the search efficiency would improve dramatically during the optimization process without tedious topology verification.To validate the proposed strategy,simulations are carried out on the test systems.The results are compared with other techniques in order to evaluate the performance of the proposed method.
基金Supported by the National Natural Science Foundation of China under Grant No.60704004the Fundamental Research Funds for the Central University under Grant No.HEUCFT1005
文摘Reconfigurability of the electrical network in a shipboard power system （SPS） after its failure is central to the restoration of power supply and improves survivability of an SPS. The navigational process creates a sequence of different operating conditions. The priority of some loads differs in changing operating conditions. After analyzing characteristics of typical SPS, a model was developed used a grade III switchboard and an environmental prioritizing agent （EPA） algorithm. This algorithm was chosen as it is logically and physically decentralized as well as multi-agent oriented. The EPA algorithm was used to decide on the dynamic load priority, then it selected the means to best meet the maximum power supply load. The simulation results showed that higher priority loads were the first to be restored. The system satisfied all necessary constraints, demonstrating the effectiveness and validity of the proposed method.
