A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users...A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.展开更多
Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the...Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.展开更多
In this paper,an intelligent constraint programming system for manufacturing material resource planning (MMRP) was presented.It is aimed to tackling large,particularly combinatorial,problems during the MMRP process,wh...In this paper,an intelligent constraint programming system for manufacturing material resource planning (MMRP) was presented.It is aimed to tackling large,particularly combinatorial,problems during the MMRP process,which increasingly involves complex sets of objectives and constraints in today’s industrial manufacturing.The system consists of a do- main-specific architecture,an algorithm library,and a pre-defined solution library,based on which intelligent agents can effi- ciently construct MMRP problem specifications,select suitable algorithms to solve problems,and evolve a population of solutions to- wards a Pareto-optimal frontier.Our system significantly improves the efficiency,effectiveness,and reliability of MMRP prob- lem solving.展开更多
This Paper presents an automatic programming system developed for NC laser onning of Chinese charaCterswhich combines AutoCAD with NC Under Windows environment, and generates numerical controlled Programs by extractin...This Paper presents an automatic programming system developed for NC laser onning of Chinese charaCterswhich combines AutoCAD with NC Under Windows environment, and generates numerical controlled Programs by extracting outline (stroke) figures of Chinese Characters from outline character base, optimizing cutting routes, transferring them to AutoCAD for editing operations, such as rotation transfer, enlarging an mirroring, the system can transferto a laser cutting machine througy RS-232 series interface to accomplish laser cutting of large Chinese characters.展开更多
Pair Programming (PP) that has gained extensive focus within pedagogical and industrial environments is a programming practice in which two programmers use the same computer to work together on analysis, design, and p...Pair Programming (PP) that has gained extensive focus within pedagogical and industrial environments is a programming practice in which two programmers use the same computer to work together on analysis, design, and programming of the same segment of code. Distributed Pair Programming (DPP) system is a programming system to aid two programmers, the driver and the navigator, to finish a common task such as analysis, design and programming on the same software from different locations. This paper first reviews the existing DPP tools and discusses the interaction and coordination mechanism in DPP process. By means of activity theory and language-action theory, some basic requirements of the DPP system are presented. Then, a design framework of such system and functions of each sub-system are deeply analyzed. Finally, a system prototype is implemented by plug-in style in Microsoft Visual Studio environment.展开更多
PARCS (Parallel Asynchronous Recursive Control System) programming tools that allow unified add-on parallel extensions over traditional programming languages are described. The PARCS model is based on the conception o...PARCS (Parallel Asynchronous Recursive Control System) programming tools that allow unified add-on parallel extensions over traditional programming languages are described. The PARCS model is based on the conception of a control space, which is used to describe parallel interacting processes. Structurally, the control space consists of addressable “points” and “channels”. Executing modules are assigned to points and communicate through channels connecting points. Recursive embeddings of processes are allowed. The effective implementation of PARCS on cloud platforms Microsoft AZURE and Amazon EC2 is also presented.展开更多
The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in futu...The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.展开更多
Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disruptin...Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.展开更多
During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.展开更多
This paper presents a broad outline and some implementation techniques of the literate programming system CDS.Compared with the previous ones(e.g.WEB,Cweb),CDS has two main characteristics: 1)A Chinese-English typeset...This paper presents a broad outline and some implementation techniques of the literate programming system CDS.Compared with the previous ones(e.g.WEB,Cweb),CDS has two main characteristics: 1)A Chinese-English typesetting system was developed to produce the documentation.This makes the Chinese documentation possible.2)A suitable method for automatic formatting was introduced to gener- ate the software documentation automatically.This frees the programmer from typesetting details while still allowing programmer's interference.展开更多
Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained u...Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously.An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained(total cost can be reduced at least 2%).展开更多
This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the b...This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the body of the dam can develop during the first impoundment of the reservoir. Although there is vast experience worldwide in CFRD design and construction, few accurate experimental relationships are available to predict the settlement in CFRD. The goal is to advance the development of intelligent methods to estimate the subsidence of dams at the design stage. Due to dam zonifieation and uncertainties in material properties, these methods appear to be the appropriate choice. In this study, the crest settlement behavior of CFRDs is analyzed based on compiled data of 24 CFRDs constructed during recent years around the world, along with the utilization of gene ex- pression programming （GEP） and adaptive neuro-fuzzy inference system （ANFIS） methods. In addition, dam height （H）, shape factor （St）, and time （t, time after first operation） are also assessed, being considered major factors in predicting the settlement behavior. From the relationships proposed, the values ofR2 for both equations of GEP （with and without constant） were 0.9603 and 0.9734, and for the three approaches of ANFIS （grid partitioning （GP）, subtractive clustering method （SCM）, and fuzzy c-means clustering （FCM）） were 0.9693, 0.8657, and 0.8848, respectively. The obtained results indicate that the overall behavior evaluated by this approach is consistent with the measured data of other CFRDs.展开更多
This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-vary...This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing in finite-horizon PI methods are discussed. Then, both data-drive n off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control.展开更多
This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method...This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.展开更多
A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking prob...A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.展开更多
In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)algorithm.First,an augmented system composed of the...In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)algorithm.First,an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented system.Next,to obtain the optimal control strategy,the stochastic case is converted into the deterministic one by system transformation,and then an ADP algorithm is proposed with convergence analysis.For the purpose of realizing the ADP algorithm,three back propagation neural networks including model network,critic network and action network are devised to guarantee unknown system model,optimal value function and optimal control strategy,respectively.Finally,the obtained optimal control strategy is applied to the original stochastic system,and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.展开更多
The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be consid...The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.展开更多
The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and test...The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and testing stages. The effect of input variables on GEP modeling was studied and 15 different GEP models with individual, binary, ternary, and quaternary input combinations were investigated. The sensitivity analysis results demonstrate that dimensionless parameter y/P, where y is the transverse coordinate, and P is the wetted perimeter, is the most influential parameter with regard to the shear stress distribution in circular channels. GEP model 10, with the parameter y/P and Reynolds number(Re) as inputs, outperformed the other GEP models, with a coefficient of determination of 0.7814 for the testing data set. An equation was derived from the best GEP model and its results were compared with an artificial neural network(ANN) model and an equation based on the Shannon entropy proposed by other researchers. The GEP model, with an average RMSE of 0.0301, exhibits superior performance over the Shannon entropy-based equation, with an average RMSE of 0.1049, and the ANN model, with an average RMSE of 0.2815 for all flow depths.展开更多
In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPS...In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.展开更多
文摘A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z2443)State Key Laboratory for Man ufacturing Systems Engineering of Xi’an Jiaotong University of China
文摘Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.
基金Founded by the Natural Science Foundation of China(50235030 and 60573080)
文摘In this paper,an intelligent constraint programming system for manufacturing material resource planning (MMRP) was presented.It is aimed to tackling large,particularly combinatorial,problems during the MMRP process,which increasingly involves complex sets of objectives and constraints in today’s industrial manufacturing.The system consists of a do- main-specific architecture,an algorithm library,and a pre-defined solution library,based on which intelligent agents can effi- ciently construct MMRP problem specifications,select suitable algorithms to solve problems,and evolve a population of solutions to- wards a Pareto-optimal frontier.Our system significantly improves the efficiency,effectiveness,and reliability of MMRP prob- lem solving.
文摘This Paper presents an automatic programming system developed for NC laser onning of Chinese charaCterswhich combines AutoCAD with NC Under Windows environment, and generates numerical controlled Programs by extracting outline (stroke) figures of Chinese Characters from outline character base, optimizing cutting routes, transferring them to AutoCAD for editing operations, such as rotation transfer, enlarging an mirroring, the system can transferto a laser cutting machine througy RS-232 series interface to accomplish laser cutting of large Chinese characters.
文摘Pair Programming (PP) that has gained extensive focus within pedagogical and industrial environments is a programming practice in which two programmers use the same computer to work together on analysis, design, and programming of the same segment of code. Distributed Pair Programming (DPP) system is a programming system to aid two programmers, the driver and the navigator, to finish a common task such as analysis, design and programming on the same software from different locations. This paper first reviews the existing DPP tools and discusses the interaction and coordination mechanism in DPP process. By means of activity theory and language-action theory, some basic requirements of the DPP system are presented. Then, a design framework of such system and functions of each sub-system are deeply analyzed. Finally, a system prototype is implemented by plug-in style in Microsoft Visual Studio environment.
文摘PARCS (Parallel Asynchronous Recursive Control System) programming tools that allow unified add-on parallel extensions over traditional programming languages are described. The PARCS model is based on the conception of a control space, which is used to describe parallel interacting processes. Structurally, the control space consists of addressable “points” and “channels”. Executing modules are assigned to points and communicate through channels connecting points. Recursive embeddings of processes are allowed. The effective implementation of PARCS on cloud platforms Microsoft AZURE and Amazon EC2 is also presented.
基金Project(2022YFC2904502)supported by the National Key Research and Development Program of ChinaProject(62273357)supported by the National Natural Science Foundation of China。
文摘The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.
基金financially supported by Ministerio de Ciencia e Innovación projects SAF2017-82736-C2-1-R to MTMFin Universidad Autónoma de Madrid and by Fundación Universidad Francisco de Vitoria to JS+2 种基金a predoctoral scholarship from Fundación Universidad Francisco de Vitoriafinancial support from a 6-month contract from Universidad Autónoma de Madrida 3-month contract from the School of Medicine of Universidad Francisco de Vitoria。
文摘Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
文摘During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.
基金This wrok was supported partly by the National Natural Science Foundationthe Ministry of Electronic Industries and High Technology Program under the National Commission of Science & Technology.
文摘This paper presents a broad outline and some implementation techniques of the literate programming system CDS.Compared with the previous ones(e.g.WEB,Cweb),CDS has two main characteristics: 1)A Chinese-English typesetting system was developed to produce the documentation.This makes the Chinese documentation possible.2)A suitable method for automatic formatting was introduced to gener- ate the software documentation automatically.This frees the programmer from typesetting details while still allowing programmer's interference.
基金supported by National Natural Science Foundation of China(61100159,61233007)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)Financial Support of the Strategic Priority Research Program of Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology and Innovation,of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid Energy Management System for Micro-smart Grid
基金Financial support from the National Natural Science Foundation of China (22022816, 22078358)。
文摘Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously.An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained(total cost can be reduced at least 2%).
文摘This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the body of the dam can develop during the first impoundment of the reservoir. Although there is vast experience worldwide in CFRD design and construction, few accurate experimental relationships are available to predict the settlement in CFRD. The goal is to advance the development of intelligent methods to estimate the subsidence of dams at the design stage. Due to dam zonifieation and uncertainties in material properties, these methods appear to be the appropriate choice. In this study, the crest settlement behavior of CFRDs is analyzed based on compiled data of 24 CFRDs constructed during recent years around the world, along with the utilization of gene ex- pression programming （GEP） and adaptive neuro-fuzzy inference system （ANFIS） methods. In addition, dam height （H）, shape factor （St）, and time （t, time after first operation） are also assessed, being considered major factors in predicting the settlement behavior. From the relationships proposed, the values ofR2 for both equations of GEP （with and without constant） were 0.9603 and 0.9734, and for the three approaches of ANFIS （grid partitioning （GP）, subtractive clustering method （SCM）, and fuzzy c-means clustering （FCM）） were 0.9693, 0.8657, and 0.8848, respectively. The obtained results indicate that the overall behavior evaluated by this approach is consistent with the measured data of other CFRDs.
基金The work of B. Pang and Z.-P. Jiang has been supported in part by the National Science Foundation (No. ECCS-1501044).
文摘This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing in finite-horizon PI methods are discussed. Then, both data-drive n off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control.
基金supported in part by the National Natural Science Foundation of China(61473070,61433004,61627809)SAPI Fundamental Research Funds(2018ZCX22)
文摘This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.
基金supported by the National Natural Science Foundation of China(Grant Nos.61034002,61233001,61273140,61304086,and 61374105)the Beijing Natural Science Foundation,China(Grant No.4132078)
文摘A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.
基金This work was supported by the National Natural Science Foundation of China(No.61873248)the Hubei Provincial Natural Science Foundation of China(Nos.2017CFA030,2015CFA010)the 111 project(No.B17040).
文摘In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)algorithm.First,an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented system.Next,to obtain the optimal control strategy,the stochastic case is converted into the deterministic one by system transformation,and then an ADP algorithm is proposed with convergence analysis.For the purpose of realizing the ADP algorithm,three back propagation neural networks including model network,critic network and action network are devised to guarantee unknown system model,optimal value function and optimal control strategy,respectively.Finally,the obtained optimal control strategy is applied to the original stochastic system,and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.
文摘The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.
文摘The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and testing stages. The effect of input variables on GEP modeling was studied and 15 different GEP models with individual, binary, ternary, and quaternary input combinations were investigated. The sensitivity analysis results demonstrate that dimensionless parameter y/P, where y is the transverse coordinate, and P is the wetted perimeter, is the most influential parameter with regard to the shear stress distribution in circular channels. GEP model 10, with the parameter y/P and Reynolds number(Re) as inputs, outperformed the other GEP models, with a coefficient of determination of 0.7814 for the testing data set. An equation was derived from the best GEP model and its results were compared with an artificial neural network(ANN) model and an equation based on the Shannon entropy proposed by other researchers. The GEP model, with an average RMSE of 0.0301, exhibits superior performance over the Shannon entropy-based equation, with an average RMSE of 0.1049, and the ANN model, with an average RMSE of 0.2815 for all flow depths.
文摘In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.
