This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are ...This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are introduced to model the interconnected systems as discrete time-space multidimensional linear systems with Markovian jumping parameters which reflect the state of communication channels. To ensure the whole system＇s well-posedness and mean square stability for a given packet loss rate, a condition is derived through analysis. Then a procedure of designing distributed dynamic output feedback controllers is proposed. The controllers have the same structure as the plants and are solved within the linear matrix inequality （LMI） framework. Finally, we apply these results to study the effect of communication losses on the multiple vehicle platoon control system, which further illustrates the effectiveness of the proposed model and method.展开更多
With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally...With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.展开更多
To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damagin...To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly described.With such method,we can avoid the inconformity of the description obtained from the traditional index systems.Three new indexes are also proposed,i.e.join index,overlap index and cover index,which help manage the relationship among several sub-weapon-networks.By normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well settled.Also,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem.Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.展开更多
Distributed stereoscopic rotating formation control of networks of second-order agents is investigated. A distributed control protocol is proposed to enable all agents to form a stereoscopic formation and surround a c...Distributed stereoscopic rotating formation control of networks of second-order agents is investigated. A distributed control protocol is proposed to enable all agents to form a stereoscopic formation and surround a common axis. Due to the existence of the rotating mode, the desired relative position between every two agents is time-varying, and a Lyapunov-based approach is employed to solve the rotating formation control problem. Finally, simulation results are provided to illustrate the effectiveness of the theoretical results.展开更多
To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.Fir...To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.展开更多
Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals.In the image application with limited resources the camera data can be stored and processed in compressed f...Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals.In the image application with limited resources the camera data can be stored and processed in compressed form.An algorithm for moving object and region detection in video using a compressive sampling is developed.The algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background scene.The algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated background.This leads to a computationally efficient method and a system compared with the existing motion estimation methods.The experimental results show that the sampling rate can reduce to 25% without sacrificing performance.展开更多
An implementation of adaptive filtering,composed of an unsupervised adaptive filter(UAF),a multi-step forward linear predictor(FLP),and an unsupervised multi-step adaptive predictor(UMAP),is built for suppressing impu...An implementation of adaptive filtering,composed of an unsupervised adaptive filter(UAF),a multi-step forward linear predictor(FLP),and an unsupervised multi-step adaptive predictor(UMAP),is built for suppressing impulsive noise in unknown circumstances.This filtering scheme,called unsupervised robust adaptive filter(URAF),possesses a switching structure,which ensures the robustness against impulsive noise.The FLP is used to detect the possible impulsive noise added to the signal,if the signal is"impulse-free",the filter UAF can estimate the clean sig-nal.If there exists impulsive noise,the impulse corrupted samples are replaced by predicted ones from the FLP,and then the UMAP estimates the clean signal.Both the simulation and experimental results show that the URAF has a better rate of convergence than the most recent universal filter,and is effective to restrict large disturbance like impulsive noise when the universal filter fails.展开更多
文摘This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are introduced to model the interconnected systems as discrete time-space multidimensional linear systems with Markovian jumping parameters which reflect the state of communication channels. To ensure the whole system＇s well-posedness and mean square stability for a given packet loss rate, a condition is derived through analysis. Then a procedure of designing distributed dynamic output feedback controllers is proposed. The controllers have the same structure as the plants and are solved within the linear matrix inequality （LMI） framework. Finally, we apply these results to study the effect of communication losses on the multiple vehicle platoon control system, which further illustrates the effectiveness of the proposed model and method.
基金supported by the National Outstanding Youth Science Foundation (60925011)the National Natural Science Foundation of China (61203181)
文摘With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.
基金Sponsored by Beijing Priority Laboratory Fund of China(SYS10070522)
文摘To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly described.With such method,we can avoid the inconformity of the description obtained from the traditional index systems.Three new indexes are also proposed,i.e.join index,overlap index and cover index,which help manage the relationship among several sub-weapon-networks.By normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well settled.Also,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem.Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.
基金supported by the National Natural Science Foundation of China(61370136)the Hainan Province Science and Technology Cooperation Fund Project(KJHZ2015-36)the Hainan Province Introduced and Integrated Demonstration Projects(YJJC20130009)
基金supported by the National Natural Science Fundation of China(61074031)
文摘Distributed stereoscopic rotating formation control of networks of second-order agents is investigated. A distributed control protocol is proposed to enable all agents to form a stereoscopic formation and surround a common axis. Due to the existence of the rotating mode, the desired relative position between every two agents is time-varying, and a Lyapunov-based approach is employed to solve the rotating formation control problem. Finally, simulation results are provided to illustrate the effectiveness of the theoretical results.
基金Project(60925011) supported by the National Natural Science Foundation for Distinguished Young Scholars of ChinaProject(9140A06040510BQXXXX) supported by Advanced Research Foundation of General Armament Department,China
文摘To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.
文摘Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals.In the image application with limited resources the camera data can be stored and processed in compressed form.An algorithm for moving object and region detection in video using a compressive sampling is developed.The algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background scene.The algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated background.This leads to a computationally efficient method and a system compared with the existing motion estimation methods.The experimental results show that the sampling rate can reduce to 25% without sacrificing performance.
基金supported by the National Science Fund for Distinguished Young Scholars of China(60925011)
文摘An implementation of adaptive filtering,composed of an unsupervised adaptive filter(UAF),a multi-step forward linear predictor(FLP),and an unsupervised multi-step adaptive predictor(UMAP),is built for suppressing impulsive noise in unknown circumstances.This filtering scheme,called unsupervised robust adaptive filter(URAF),possesses a switching structure,which ensures the robustness against impulsive noise.The FLP is used to detect the possible impulsive noise added to the signal,if the signal is"impulse-free",the filter UAF can estimate the clean sig-nal.If there exists impulsive noise,the impulse corrupted samples are replaced by predicted ones from the FLP,and then the UMAP estimates the clean signal.Both the simulation and experimental results show that the URAF has a better rate of convergence than the most recent universal filter,and is effective to restrict large disturbance like impulsive noise when the universal filter fails.
