Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties ...Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.展开更多
Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inp...Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural networks.In this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training RVFL.The link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is analyzed.The experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.展开更多
Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are designed.Their closed-loop ...Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are designed.Their closed-loop systems and control increments are derived,respectively.展开更多
At present, the studies on multi-team antagonistic games(MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also select...At present, the studies on multi-team antagonistic games(MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets.Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information(DMTAGII) model.For this model, the corresponding concept of perfect Bayesian Nash equilibrium(PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles(UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm.Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems.展开更多
Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Cons...Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined,this paper proposes a long short-term memory based(LSTM-based)framework that combines intention prediction and trajectory prediction together.First,we build an intersection prior trajectories model(IPTM)by clustering and statistically analyzing a large number of prior traffic flow trajectories.The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory,and also serves as a reference for credibility evaluation.Second,we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage.Furthermore,the predicted intention is also a key that is associated with the prior trajectories model.The proposed framework is validated on two publically released datasets,next generation simulation(NGSIM)and INTERACTION.Compared with other prediction methods,our framework is able to sample a trajectory from the estimated distribution,with its accuracy improved by about 20%.Finally,the credibility evaluation,which is based on the prior trajectories model,makes the framework more practical in the real-world applications.展开更多
Image classification based on bag-of-words(BOW)has a broad application prospect in pattern recognition field but the shortcomings such as single feature and low classification accuracy are apparent.To deal with this...Image classification based on bag-of-words(BOW)has a broad application prospect in pattern recognition field but the shortcomings such as single feature and low classification accuracy are apparent.To deal with this problem,this paper proposes to combine two ingredients:(i)Three features with functions of mutual complementation are adopted to describe the images,including pyramid histogram of words(PHOW),pyramid histogram of color(PHOC)and pyramid histogram of orientated gradients(PHOG).(ii)An adaptive feature-weight adjusted image categorization algorithm based on the SVM and the decision level fusion of multiple features are employed.Experiments are carried out on the Caltech101 database,which confirms the validity of the proposed approach.The experimental results show that the classification accuracy rate of the proposed method is improved by 7%-14%higher than that of the traditional BOW methods.With full utilization of global,local and spatial information,the algorithm is much more complete and flexible to describe the feature information of the image through the multi-feature fusion and the pyramid structure composed by image spatial multi-resolution decomposition.Significant improvements to the classification accuracy are achieved as the result.展开更多
This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system coordination.The controllability of nonholonomic system,the control met...This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system coordination.The controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,respectively.Some important definitions,lemmas,theorems and dynamics are elaborated.Both the consensus and formation control problems for networked nonholonomic chained systems are summarised.Finally,some open questions are proposed.展开更多
Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data...Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine.展开更多
A nonlinear robust trajectory tracking strategy for a gliding hypersonic vehicle with an aileron stuck at an unknown position is presented in this paper. First, the components of translational motion dynamics perpendi...A nonlinear robust trajectory tracking strategy for a gliding hypersonic vehicle with an aileron stuck at an unknown position is presented in this paper. First, the components of translational motion dynamics perpendicular to the velocity are derived, and then a guidance law based on a time-varying sliding mode method is used to realize trajectory tracking. Furthermore, the rotational equations of motion are separated into an actuated subsystem and an unactuated subsystem. And an adaptive time-varying sliding mode attitude controller is proposed based on the actuated subsystem to track the command attitude and the tracking performance and robustness are therefore enhanced. The proposed guidance law and attitude controller make the hypersonic vehicle fly along the reference trajectory even when the aileron is stuck at an unknown angle. Finally, a hypersonic benchmark platform is used to demonstrate the effectiveness of the proposed strategy.展开更多
The optimal path planning for fixed-wing unmanned aerial vehicles(UAVs) in multi-target surveillance tasks(MTST) in the presence of wind is concerned.To take into account the minimal turning radius of UAVs,the Dubins ...The optimal path planning for fixed-wing unmanned aerial vehicles(UAVs) in multi-target surveillance tasks(MTST) in the presence of wind is concerned.To take into account the minimal turning radius of UAVs,the Dubins model is used to approximate the dynamics of UAVs.Based on the assumption,the path planning problem of UAVs in MTST can be formulated as a Dubins traveling salesman problem(DTSP).By considering its prohibitively high computational cost,the Dubins paths under terminal heading relaxation are introduced,which leads to significant reduction of the optimization scale and difficulty of the whole problem.Meanwhile,in view of the impact of wind on UAVs' paths,the notion of virtual target is proposed.The application of the idea successfully converts the Dubins path planning problem from an initial configuration to a target in wind into a problem of finding the minimal root of a transcendental equation.Then,the Dubins tour is derived by using differential evolution(DE) algorithm which employs random-key encoding technique to optimize the visiting sequence of waypoints.Finally,the effectiveness and efficiency of the proposed algorithm are demonstrated through computational experiments.Numerical results exhibit that the proposed algorithm can produce high quality solutions to the problem.展开更多
Splenic artery aneurysm, without obvious symptoms, is a direct threat to the patient's life, once it ruptures as hemorrhagic shock.Imaging examinations have been the main diagnostic methods of splenic artery aneurysm...Splenic artery aneurysm, without obvious symptoms, is a direct threat to the patient's life, once it ruptures as hemorrhagic shock.Imaging examinations have been the main diagnostic methods of splenic artery aneurysm, including ultrasound, computed tomography (CT), magnetic resonance imaging, and digital subtraction angiography (DSA).Although various inspective methods have their own advantages and disadvantages, abdominal CT examination is the most comprehensively applied method in clinical settings.The representative images of splenic artery aneurysm from a relatively large number of patients examined by CT are presented in this study.展开更多
Nonlinearity is ubiquitous in engineering and natural systems.The development of nonlinear control can be traced back to decades ago.To date,the research has reached the stage that emphasizes developing methodologies ...Nonlinearity is ubiquitous in engineering and natural systems.The development of nonlinear control can be traced back to decades ago.To date,the research has reached the stage that emphasizes developing methodologies that can handle the complexity characterized by uncertainty,展开更多
The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so...The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs' minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN). Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario). The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.展开更多
Salvo attacking a surface target by multiple missiles is an effective tactic to enhance the lethality and penetrate the defense system. However, existing cooperative guidance laws in the midcourse or terminal course a...Salvo attacking a surface target by multiple missiles is an effective tactic to enhance the lethality and penetrate the defense system. However, existing cooperative guidance laws in the midcourse or terminal course are not suitable for long-and medium-range missiles or stand-off attacking. Because the initial conditions of cooperative terminal guidance that are generally generated from the mid-course flight may not lead to a successful cooperative terminal guidance without proper mid-course flight adjustment. Meanwhile, cooperative guidance in the mid-course cannot solely guarantee the accuracy of a simultaneous arrival of multiple missiles. Therefore, a joint mid-course and terminal course cooperative guidance law is developed. By building a distinct leader-follower framework, this paper proposes an efficient coordinated Dubins path planning method to synchronize the arrival time of all engaged missiles in the mid-course flight. The planned flight can generate proper initial conditions for cooperative terminal guidance, and also benefit an earliest simultaneous arrival. In the terminal course, an existing cooperative proportional navigation guidance law guides all the engaged missiles to arrive at a target accurately and simultaneously.The integrated guidance law for an intuitive application is summarized. Simulations demonstrate that the proposed method can generate fast and accurate salvo attack.展开更多
As a cutting-edge branch of unmanned aerial vehicle(UAV)technology,the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors,due to its remarkable merits in functionali...As a cutting-edge branch of unmanned aerial vehicle(UAV)technology,the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors,due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks,e.g.,search and rescue,fire-fighting,reconnaissance,and surveillance.Cooperative path planning(CPP)is a key problem for a UAV group in executing tasks collectively.In this paper,an attempt is made to perform a comprehensive review of the research on CPP for UAV groups.First,a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements,i.e.,task,UAV group,and environment,as a basis for a comprehensive classification of different types of CPP problems.By following the proposed framework,a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified way.Then,a review and a statistical analysis are presented based on the taxonomy,emphasizing the coordinative elements in the existing CPP research.In addition,a collection of challenging CPP problems are provided to highlight future research directions.展开更多
For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively....For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively. In this study, a class of discrete-time switched systems with unmodeled dynamics is taken into consideration. Moreover, nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper, and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance. For robustness against unmodeled dynamics and uncertainty, robust model reference adaptive control(RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems. Meanwhile, two different switching laws are presented for switched systems and nonlinear systems, respectively. Thereby, the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems. Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes. Furthermore, as to the proposed scheme for nonlinear systems, its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.展开更多
In recent years,cyber-physical systems(CPSs)have received much attention from both the academic world and the industrial world,which refer to a deep integration and coordination of physical and computational resources...In recent years,cyber-physical systems(CPSs)have received much attention from both the academic world and the industrial world,which refer to a deep integration and coordination of physical and computational resources[1,2].Typical examples of CPSs can be found in smart grids,smart transportation systems,industrial control systems,water supply systems,and so on.Furthermore,many military systems展开更多
Because of their wide detection range and rich functions,autonomous underwater vehicles(AUVs)are widely used for observing the marine environment,for exploring natural resources,for security and defense purposes,and i...Because of their wide detection range and rich functions,autonomous underwater vehicles(AUVs)are widely used for observing the marine environment,for exploring natural resources,for security and defense purposes,and in many other fields of interest.Compared with a single AUV,a multi-AUV formation can better perform various tasks and adapt to complex underwater environments.With changes in the mission or environment,a change in the UAV formation may also be required.In the last decade,much progress has been made in the transformation of multi-AUV formations.In this paper,we aim to analyze the core concepts of multi-AUV formation transformation;summarize the effects of the AUV model,underwater environment,and communication between AUVs within formations on formation transformation;and elaborate on basic theories and implementation approaches for multi-AUV formation transformation.Moreover,this overview includes a bibliometric analysis of the related literature from multiple perspectives.Finally,some challenging issues and future research directions for multi-AUV formation transformation are highlighted.展开更多
基金supported by the National Natural Science Foundation of China (6202201562088101)+1 种基金Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100)Shanghai Municip al Commission of Science and Technology Project (19511132101)。
文摘Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.
基金supported by the Ministry of Science and Technology of China(2018AAA0101000,2017YFF0205306,WQ20141100198)the National Natural Science Foundation of China(91648117)。
文摘Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected.Their network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural networks.In this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training RVFL.The link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is analyzed.The experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.
基金the National Natural Science Foundation of China(62173002,61925303,62088101,U20B2073,61720106011,62173255)the National Key R&D Program of China(2018YFC0809700)the Beijing Natural Science Foundation(4222045)。
文摘Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are designed.Their closed-loop systems and control increments are derived,respectively.
基金supported by Foundation for Innovative Research Groups of National Natural Science Foundation of China(NSFC)(61321002)National Science Fund for Distinguished Young Scholars(60925011)+2 种基金Projects of Major International(Regional)Joint Research Program NSFC(61120106010)Beijing Education Committee Cooperation Building Foundation Project,Program for Changjiang Scholars and Innovative Research Team in University(IRT1208)Chang Jiang Scholars Program and National Natural Science Foundation of China(61203078)
文摘At present, the studies on multi-team antagonistic games(MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets.Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information(DMTAGII) model.For this model, the corresponding concept of perfect Bayesian Nash equilibrium(PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles(UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm.Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems.
基金partly supported by the National Natural Science Foundation of China(61903034,U1913203,61973034,91120003)the Program for Changjiang Scholars and Innovative Research Team in University(IRT-16R06,T2014224)+1 种基金China Postdoctoral Science Foundation funded project(2019TQ0035)Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined,this paper proposes a long short-term memory based(LSTM-based)framework that combines intention prediction and trajectory prediction together.First,we build an intersection prior trajectories model(IPTM)by clustering and statistically analyzing a large number of prior traffic flow trajectories.The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory,and also serves as a reference for credibility evaluation.Second,we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage.Furthermore,the predicted intention is also a key that is associated with the prior trajectories model.The proposed framework is validated on two publically released datasets,next generation simulation(NGSIM)and INTERACTION.Compared with other prediction methods,our framework is able to sample a trajectory from the estimated distribution,with its accuracy improved by about 20%.Finally,the credibility evaluation,which is based on the prior trajectories model,makes the framework more practical in the real-world applications.
基金Supported by Foundation for Innovative Research Groups of the National Natural Science Foundation of China(61321002)Projects of Major International(Regional)Jiont Research Program NSFC(61120106010)+1 种基金Beijing Education Committee Cooperation Building Foundation ProjectProgram for Changjiang Scholars and Innovative Research Team in University(IRT1208)
文摘Image classification based on bag-of-words(BOW)has a broad application prospect in pattern recognition field but the shortcomings such as single feature and low classification accuracy are apparent.To deal with this problem,this paper proposes to combine two ingredients:(i)Three features with functions of mutual complementation are adopted to describe the images,including pyramid histogram of words(PHOW),pyramid histogram of color(PHOC)and pyramid histogram of orientated gradients(PHOG).(ii)An adaptive feature-weight adjusted image categorization algorithm based on the SVM and the decision level fusion of multiple features are employed.Experiments are carried out on the Caltech101 database,which confirms the validity of the proposed approach.The experimental results show that the classification accuracy rate of the proposed method is improved by 7%-14%higher than that of the traditional BOW methods.With full utilization of global,local and spatial information,the algorithm is much more complete and flexible to describe the feature information of the image through the multi-feature fusion and the pyramid structure composed by image spatial multi-resolution decomposition.Significant improvements to the classification accuracy are achieved as the result.
基金supported in part by the National Natural Science Foundation of China under[grant number 61321002],[grant number 61120106010],[grant number 61175112]the programme for New Century Excellent Talents in University+1 种基金the Social Science Foundation of Fujian Province under[grant number 2014B182]the Beijing Education Committee Cooperation Building Foundation Project.
文摘This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system coordination.The controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,respectively.Some important definitions,lemmas,theorems and dynamics are elaborated.Both the consensus and formation control problems for networked nonholonomic chained systems are summarised.Finally,some open questions are proposed.
文摘Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine.
文摘A nonlinear robust trajectory tracking strategy for a gliding hypersonic vehicle with an aileron stuck at an unknown position is presented in this paper. First, the components of translational motion dynamics perpendicular to the velocity are derived, and then a guidance law based on a time-varying sliding mode method is used to realize trajectory tracking. Furthermore, the rotational equations of motion are separated into an actuated subsystem and an unactuated subsystem. And an adaptive time-varying sliding mode attitude controller is proposed based on the actuated subsystem to track the command attitude and the tracking performance and robustness are therefore enhanced. The proposed guidance law and attitude controller make the hypersonic vehicle fly along the reference trajectory even when the aileron is stuck at an unknown angle. Finally, a hypersonic benchmark platform is used to demonstrate the effectiveness of the proposed strategy.
基金Project(61120106010)supported by the Projects of Major International(Regional)Joint Research Program Nature Science Foundation of ChinaProject(61304215,61203078)supported by National Natural Science Foundation of China+1 种基金Project(2013000704)supported by the Beijing Outstanding Ph.D.Program Mentor,ChinaProject(61321002)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China
文摘The optimal path planning for fixed-wing unmanned aerial vehicles(UAVs) in multi-target surveillance tasks(MTST) in the presence of wind is concerned.To take into account the minimal turning radius of UAVs,the Dubins model is used to approximate the dynamics of UAVs.Based on the assumption,the path planning problem of UAVs in MTST can be formulated as a Dubins traveling salesman problem(DTSP).By considering its prohibitively high computational cost,the Dubins paths under terminal heading relaxation are introduced,which leads to significant reduction of the optimization scale and difficulty of the whole problem.Meanwhile,in view of the impact of wind on UAVs' paths,the notion of virtual target is proposed.The application of the idea successfully converts the Dubins path planning problem from an initial configuration to a target in wind into a problem of finding the minimal root of a transcendental equation.Then,the Dubins tour is derived by using differential evolution(DE) algorithm which employs random-key encoding technique to optimize the visiting sequence of waypoints.Finally,the effectiveness and efficiency of the proposed algorithm are demonstrated through computational experiments.Numerical results exhibit that the proposed algorithm can produce high quality solutions to the problem.
文摘Splenic artery aneurysm, without obvious symptoms, is a direct threat to the patient's life, once it ruptures as hemorrhagic shock.Imaging examinations have been the main diagnostic methods of splenic artery aneurysm, including ultrasound, computed tomography (CT), magnetic resonance imaging, and digital subtraction angiography (DSA).Although various inspective methods have their own advantages and disadvantages, abdominal CT examination is the most comprehensively applied method in clinical settings.The representative images of splenic artery aneurysm from a relatively large number of patients examined by CT are presented in this study.
文摘Nonlinearity is ubiquitous in engineering and natural systems.The development of nonlinear control can be traced back to decades ago.To date,the research has reached the stage that emphasizes developing methodologies that can handle the complexity characterized by uncertainty,
基金co-supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 61321002)the Projects of Major International (Regional) Joint Research Program NSFC (No. 61120106010)+1 种基金Beijing Education Committee Cooperation Building Foundation Project, the National Natural Science Foundation of China (No. 61304215)Beijing Outstanding Ph.D. Program Mentor (No. 20131000704)
文摘The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles (UAVs) performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs' minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood (DTSPN). Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants (multi-UAV scenario and multiple groups of targets scenario). The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.
基金supported by the National Natural Science Foundation of China (No.61304215)supported by the Beijing Education Committee Cooperation Building Foundation Project (CSYS100070417)
文摘Salvo attacking a surface target by multiple missiles is an effective tactic to enhance the lethality and penetrate the defense system. However, existing cooperative guidance laws in the midcourse or terminal course are not suitable for long-and medium-range missiles or stand-off attacking. Because the initial conditions of cooperative terminal guidance that are generally generated from the mid-course flight may not lead to a successful cooperative terminal guidance without proper mid-course flight adjustment. Meanwhile, cooperative guidance in the mid-course cannot solely guarantee the accuracy of a simultaneous arrival of multiple missiles. Therefore, a joint mid-course and terminal course cooperative guidance law is developed. By building a distinct leader-follower framework, this paper proposes an efficient coordinated Dubins path planning method to synchronize the arrival time of all engaged missiles in the mid-course flight. The planned flight can generate proper initial conditions for cooperative terminal guidance, and also benefit an earliest simultaneous arrival. In the terminal course, an existing cooperative proportional navigation guidance law guides all the engaged missiles to arrive at a target accurately and simultaneously.The integrated guidance law for an intuitive application is summarized. Simulations demonstrate that the proposed method can generate fast and accurate salvo attack.
基金Project supported by the National Natural Science Foundation of China(Nos.61822304,61673058,61621063,61720106011,and62088101)the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(No.U1609214)+1 种基金the Consulting Research Project of the Chinese Academy of Engineering(No.2019-XZ-7)the Beijing Advanced Innovation Center for Intelligent Robots and Systems,and the Peng Cheng Laboratory。
文摘As a cutting-edge branch of unmanned aerial vehicle(UAV)technology,the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors,due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks,e.g.,search and rescue,fire-fighting,reconnaissance,and surveillance.Cooperative path planning(CPP)is a key problem for a UAV group in executing tasks collectively.In this paper,an attempt is made to perform a comprehensive review of the research on CPP for UAV groups.First,a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements,i.e.,task,UAV group,and environment,as a basis for a comprehensive classification of different types of CPP problems.By following the proposed framework,a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified way.Then,a review and a statistical analysis are presented based on the taxonomy,emphasizing the coordinative elements in the existing CPP research.In addition,a collection of challenging CPP problems are provided to highlight future research directions.
基金supported by Deep Exploration Technology and Experimentation Project under Grant No.201311194-04partially supported by the National Natural Science Foundation of China under Grant Nos.61321002 and 61473038+1 种基金Beijing Outstanding Talents Programme under Grant No.2012D009011000003Graduate Teaching/Innovation Funding of Beijing Institute of Technology
文摘For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively. In this study, a class of discrete-time switched systems with unmodeled dynamics is taken into consideration. Moreover, nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper, and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance. For robustness against unmodeled dynamics and uncertainty, robust model reference adaptive control(RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems. Meanwhile, two different switching laws are presented for switched systems and nonlinear systems, respectively. Thereby, the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems. Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes. Furthermore, as to the proposed scheme for nonlinear systems, its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.
基金supported by the National Natural Science Foundation of China(Grant Nos.61522303,U1509215&61621063)Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT1208)
文摘In recent years,cyber-physical systems(CPSs)have received much attention from both the academic world and the industrial world,which refer to a deep integration and coordination of physical and computational resources[1,2].Typical examples of CPSs can be found in smart grids,smart transportation systems,industrial control systems,water supply systems,and so on.Furthermore,many military systems
基金Support Program(No.61822304)the Basic Science Center Programs of NSFC(No.62088101)+2 种基金the Peng Cheng Laboratory,the Consulting Research Project of the Chinese Academy of Engineering(No.2019-XZ-7)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.61621063)the Projects of Major International(Regional)Joint Research Program of NSFC(No.61720106011).
文摘Because of their wide detection range and rich functions,autonomous underwater vehicles(AUVs)are widely used for observing the marine environment,for exploring natural resources,for security and defense purposes,and in many other fields of interest.Compared with a single AUV,a multi-AUV formation can better perform various tasks and adapt to complex underwater environments.With changes in the mission or environment,a change in the UAV formation may also be required.In the last decade,much progress has been made in the transformation of multi-AUV formations.In this paper,we aim to analyze the core concepts of multi-AUV formation transformation;summarize the effects of the AUV model,underwater environment,and communication between AUVs within formations on formation transformation;and elaborate on basic theories and implementation approaches for multi-AUV formation transformation.Moreover,this overview includes a bibliometric analysis of the related literature from multiple perspectives.Finally,some challenging issues and future research directions for multi-AUV formation transformation are highlighted.