This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration s...This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.展开更多
Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage...Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed.On the basis of the expert reagent regulation method in antimony flotation process,the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning.Then,the sensitivity index is used to calculate the key features of reagent dosage.The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process.At last,the prediction model is used to finish the classification and discriminant analysis.The simulation results and industrial experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage.It can lay a foundation for optimizing the whole process of flotation.展开更多
Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is t...Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.展开更多
A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism a...A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.展开更多
The coordinated Bayesian optimization algorithm(CBOA) is proposed according to the characteristics of the function independence,conformity and supplementary between the electronic countermeasure(ECM) and the firep...The coordinated Bayesian optimization algorithm(CBOA) is proposed according to the characteristics of the function independence,conformity and supplementary between the electronic countermeasure(ECM) and the firepower attack systems.The selection criteria are combinations of probabilities of individual fitness and coordinated degree and can select choiceness individual to construct Bayesian network that manifest population evolution by producing the new chromosome.Thus the CBOA cannot only guarantee the effective pattern coordinated decision-making mechanism between the populations,but also maintain the population multiplicity,and enhance the algorithm performance.The simulation result confirms the algorithm validity.展开更多
In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of ...Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of coordinating protective relays in electrical power systems consists of selecting suitable settings such that their fundamental protective function is met,given operational requirements of sensitivity,selectivity,reliability and speed.Directional over current relays are best suited for protection of an interconnected sub-station transmission system.One of the major problems associated with this type of protection is the difficulty in coordinating relays.To insure proper coordination,all the main/back up relay pairs must be determined.This paper presents an effective algorithm to determine the minimum number of break points and main/back up relay pairs using relative sequence matrix(RSM).A novel optimization technique based on evolutionary programming was developed using these main/back up relay pairs for directional over current relay coordination in multi-loop networks.Since the problem has multi-optimum points,conventional mathematics based optimization techniques may sometimes fail.Hence evolutionary programming(EP) was used,as it is a stochastic multi-point search optimization algorithm capable of escaping from the local optimum problem,giving a better chance of reaching a global optimum.The method developed was tested on an existing 6 bus,7 line system and better results were obtained than with conventional methods.展开更多
基金funded by the National Natural Science Foundation of China(12102487)Basic and Applied Basic Research Foundation of Guangdong Province,China(2023A1515012339)+1 种基金Shenzhen Science and Technology Program(ZDSYS20210623091808026)the Discovery Grant(RGPIN-2024-06290)of the Natural Sciences and Engineering Research Council of Canada。
文摘This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.
基金Project(61725306)supported by the National Science Foundation for Distinguished Young Scholars of ChinaProjects(61473318,61403136,61703157,61751312)supported by the National Natural Science Foundation of ChinaProject(16C0940)supported by Foundation of Hunan Educational Committee,China
文摘Considering the influence of reagent adjustment in different flotation bank on the final production index and the difficulty of establishing an effective mathematical model,a coordinated optimization method for dosage reagent based on key characteristics variation tendency and case-based reasoning is proposed.On the basis of the expert reagent regulation method in antimony flotation process,the reagent dosage pre-setting model of the roughing–scavenging bank is constructed based on case-based reasoning.Then,the sensitivity index is used to calculate the key features of reagent dosage.The reagent dosage compensation model is constructed based on the variation tendency of the key features in the roughing and scavenging process.At last,the prediction model is used to finish the classification and discriminant analysis.The simulation results and industrial experiment in antimony flotation process show that the proposed method reduces fluctuation of the tailings indicators and the cost of reagent dosage.It can lay a foundation for optimizing the whole process of flotation.
文摘Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.
基金Project(2002CB312203) supported by the National Key Fundamental Research and Development Programof China pro-ject(60574030) supported bythe National Natural Science Foundation of China project(06FD026) supported bythe Natural Science Foun-dation of Hunan Province , China
文摘A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.
基金supported by the National Natural Science Foundation of China (10377014)the Innovation Foundation of Northwestern Polytechnical university (2007KJ01027)
文摘The coordinated Bayesian optimization algorithm(CBOA) is proposed according to the characteristics of the function independence,conformity and supplementary between the electronic countermeasure(ECM) and the firepower attack systems.The selection criteria are combinations of probabilities of individual fitness and coordinated degree and can select choiceness individual to construct Bayesian network that manifest population evolution by producing the new chromosome.Thus the CBOA cannot only guarantee the effective pattern coordinated decision-making mechanism between the populations,but also maintain the population multiplicity,and enhance the algorithm performance.The simulation result confirms the algorithm validity.
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
文摘Co-ordination of directional over current relays(DOCR) requires the selection and setting of relays so as to sequentially isolate only that portion of the power system where an abnormality has occurred.The problem of coordinating protective relays in electrical power systems consists of selecting suitable settings such that their fundamental protective function is met,given operational requirements of sensitivity,selectivity,reliability and speed.Directional over current relays are best suited for protection of an interconnected sub-station transmission system.One of the major problems associated with this type of protection is the difficulty in coordinating relays.To insure proper coordination,all the main/back up relay pairs must be determined.This paper presents an effective algorithm to determine the minimum number of break points and main/back up relay pairs using relative sequence matrix(RSM).A novel optimization technique based on evolutionary programming was developed using these main/back up relay pairs for directional over current relay coordination in multi-loop networks.Since the problem has multi-optimum points,conventional mathematics based optimization techniques may sometimes fail.Hence evolutionary programming(EP) was used,as it is a stochastic multi-point search optimization algorithm capable of escaping from the local optimum problem,giving a better chance of reaching a global optimum.The method developed was tested on an existing 6 bus,7 line system and better results were obtained than with conventional methods.