This paper proposes the assumption that the flow with viscous friction is the stretch of part of the sheet that lies along the walls of a die during the process of superplastic bulging according to superplastic flow e...This paper proposes the assumption that the flow with viscous friction is the stretch of part of the sheet that lies along the walls of a die during the process of superplastic bulging according to superplastic flow equation and geometrical model of bulging of a sheet into a long trapezoid groove or truncated cone, by introducing the friction-factor P which describes the friction effect on the process. Also, the paper proposes the method of controlling thickness nonuniformity and develops the equipment which for uniform thickness of bulging, is automatically controlled with a computerl it also analyzes the important innuence of lubrication on thickness distribution of bulging materials. By the assumption, the relationship between bulging pressure and time is obtained in bulging of a sheet into the groove and cone, and p-t curve of multi-mould-cavity complicated bulging is discussed based on the analysis of single-mould-cavity bulging characteristics.展开更多
I present a new scheme for probabilistic remote preparation of a general two-qubit state from a sender to either of two receivers.The quantum channel is composed of a partial entangled tripartite Greenberger-Horne-Zei...I present a new scheme for probabilistic remote preparation of a general two-qubit state from a sender to either of two receivers.The quantum channel is composed of a partial entangled tripartite Greenberger-Horne-Zeilinger (GHZ) state and a W-type state.I try to realize the remote two-qubit preparation by using the usual projective measurement and the method of positive operator-valued measure,respectively.The corresponding success probabilities of the scheme with different methods as well as the total classical communication cost required in this scheme are also calculated.展开更多
Remote control process system with distributed time-delay has attracted much attention in different fields.In this paper,non-linear remote control of a single tank process system with wireless network is considered.To...Remote control process system with distributed time-delay has attracted much attention in different fields.In this paper,non-linear remote control of a single tank process system with wireless network is considered.To deal with the distributed time-delay in a large-scale plant,the time-delay compensation controller based on DCS devices is designed by using operator theory and particle filter.Distributed control system(DCS)device is developed to monitor and control from the central monitoring room to each process.The particle filter is a probabilistic method to estimate unobservable information from observable information.First,remote control system and experimental equipment are introduced.Second,control system based on an operator theory is designed.Then,process system with distributed time-delay using particle filter is carried out.Finally,the actual experiment is conducted by using the proposed time-delay compensation controller.When estimating with the proposed method,the result is close to the case in which the distributed time-delay does not exist.The effectiveness of the proposed control system is confirmed by experiment results.展开更多
Coverage challenge for small considered to be a optlmlzation is a main cell clusters which are promising solution to provide seamless cellular coverage for large indoor or outdoor areas. This paper focuses on small ce...Coverage challenge for small considered to be a optlmlzation is a main cell clusters which are promising solution to provide seamless cellular coverage for large indoor or outdoor areas. This paper focuses on small cell cluster coverage problems and proposes both centralized and distributed self-optimization methods. Modified Particle swarm optimization （MPSO） is introduced to centralized optimization which employs particle swarm optimization （PSO） and introduces a heuristic power control scheme to accelerate the algorithm to search tbr the global optimum solution. Distributed coverage optimization is modeled as a non-cooperative game, with a utility function considering both throughput and interference. An iterative power control algorithm is then proposed using game theory （DGT） which converges to Nash Equilibrium （NE）. Simulation results show that both MPSO and DGT have excellent performance in coverage optimization and outperform optimization using simulated annealing algorithm （SA）, reaching higher coverage ratio and throughput while with less iterations.展开更多
Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which...Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.展开更多
A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural...A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem,lifting-rope subsystem and anti-swing subsystem.Then,the parameters of the controller were optimized with PSO to enable the system to have good dynamic performances.During the process of high-speed load hoisting and dropping,this method can not only realize the accurate position of the trolley and eliminate the sway of the load in spite of existing uncertainties,and the maximum swing angle is only ±0.1 rad,but also completely eliminate the chattering of conventional sliding mode control and improve the robustness of system.The simulation results show the correctness and validity of this method.展开更多
文摘This paper proposes the assumption that the flow with viscous friction is the stretch of part of the sheet that lies along the walls of a die during the process of superplastic bulging according to superplastic flow equation and geometrical model of bulging of a sheet into a long trapezoid groove or truncated cone, by introducing the friction-factor P which describes the friction effect on the process. Also, the paper proposes the method of controlling thickness nonuniformity and develops the equipment which for uniform thickness of bulging, is automatically controlled with a computerl it also analyzes the important innuence of lubrication on thickness distribution of bulging materials. By the assumption, the relationship between bulging pressure and time is obtained in bulging of a sheet into the groove and cone, and p-t curve of multi-mould-cavity complicated bulging is discussed based on the analysis of single-mould-cavity bulging characteristics.
基金Supported by the 211 Project of Anhui University under Grant No.2009QN028B
文摘I present a new scheme for probabilistic remote preparation of a general two-qubit state from a sender to either of two receivers.The quantum channel is composed of a partial entangled tripartite Greenberger-Horne-Zeilinger (GHZ) state and a W-type state.I try to realize the remote two-qubit preparation by using the usual projective measurement and the method of positive operator-valued measure,respectively.The corresponding success probabilities of the scheme with different methods as well as the total classical communication cost required in this scheme are also calculated.
基金Project(K117K06225)supported by JSPS KAKENHI,Japan
文摘Remote control process system with distributed time-delay has attracted much attention in different fields.In this paper,non-linear remote control of a single tank process system with wireless network is considered.To deal with the distributed time-delay in a large-scale plant,the time-delay compensation controller based on DCS devices is designed by using operator theory and particle filter.Distributed control system(DCS)device is developed to monitor and control from the central monitoring room to each process.The particle filter is a probabilistic method to estimate unobservable information from observable information.First,remote control system and experimental equipment are introduced.Second,control system based on an operator theory is designed.Then,process system with distributed time-delay using particle filter is carried out.Finally,the actual experiment is conducted by using the proposed time-delay compensation controller.When estimating with the proposed method,the result is close to the case in which the distributed time-delay does not exist.The effectiveness of the proposed control system is confirmed by experiment results.
基金supported by the National High-Tech Development 863 Program of China (Grant DOS. 2012AA012801)National Natural Science Foundation of China(No.61331009)
文摘Coverage challenge for small considered to be a optlmlzation is a main cell clusters which are promising solution to provide seamless cellular coverage for large indoor or outdoor areas. This paper focuses on small cell cluster coverage problems and proposes both centralized and distributed self-optimization methods. Modified Particle swarm optimization （MPSO） is introduced to centralized optimization which employs particle swarm optimization （PSO） and introduces a heuristic power control scheme to accelerate the algorithm to search tbr the global optimum solution. Distributed coverage optimization is modeled as a non-cooperative game, with a utility function considering both throughput and interference. An iterative power control algorithm is then proposed using game theory （DGT） which converges to Nash Equilibrium （NE）. Simulation results show that both MPSO and DGT have excellent performance in coverage optimization and outperform optimization using simulated annealing algorithm （SA）, reaching higher coverage ratio and throughput while with less iterations.
基金Project(NS2013091)supported by the Basis Research Fund of Nanjing University of Aeronautics and Astronautics,China
文摘Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.
基金Project(51075289) supported by the National Natural Science Foundation of ChinaProject(20122014) supported by the Doctor Foundation of Taiyuan University of Science and Technology,China
文摘A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem,lifting-rope subsystem and anti-swing subsystem.Then,the parameters of the controller were optimized with PSO to enable the system to have good dynamic performances.During the process of high-speed load hoisting and dropping,this method can not only realize the accurate position of the trolley and eliminate the sway of the load in spite of existing uncertainties,and the maximum swing angle is only ±0.1 rad,but also completely eliminate the chattering of conventional sliding mode control and improve the robustness of system.The simulation results show the correctness and validity of this method.
