The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms ...The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.展开更多
Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission sche...Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission scheme for an AirCompbased FL system with imperfect channel state information(CSI)is proposed.To model CSI uncertainty,an expectation-based error model is utilized.The main objective is to maximize the number of selected devices that meet mean-squared error(MSE)requirements for model broadcast and model aggregation.The problem is formulated as a combinatorial optimization problem and is solved in two steps.First,the priority order of devices is determined by a sparsity-inducing procedure.Then,a feasibility detection scheme is used to select the maximum number of devices to guarantee that the MSE requirements are met.An alternating optimization(AO)scheme is used to transform the resulting nonconvex problem into two convex subproblems.Numerical results illustrate the effectiveness and robustness of the proposed scheme.展开更多
To increase the robustness of the optimization solutions of the mixed-flow pump,the impeller was firstly indirectly parameterized based on the 2D blade design theory.Secondly,the robustness of the optimization solutio...To increase the robustness of the optimization solutions of the mixed-flow pump,the impeller was firstly indirectly parameterized based on the 2D blade design theory.Secondly,the robustness of the optimization solution was mathematically defined,and then calculated by Monte Carlo sampling method.Thirdly,the optimization on the mixed-flow pump′s impeller was decomposed into the optimal and robust sub-optimization problems,to maximize the pump head and efficiency and minimize the fluctuation degree of them under varying working conditions at the same time.Fourthly,using response surface model,a surrogate model was established between the optimization objectives and control variables of the shape of the impeller.Finally,based on a multi-objective genetic optimization algorithm,a two-loop iterative optimization process was designed to find the optimal solution with good robustness.Comparing the original and optimized pump,it is found that the internal flow field of the optimized pump has been improved under various operating conditions,the hydraulic performance has been improved consequently,and the range of high efficient zone has also been widened.Besides,with the changing of working conditions,the change trend of the hydraulic performance of the optimized pump becomes gentler,the flow field distribution is more uniform,and the influence degree of the varia-tion of working conditions decreases,and the operating stability of the pump is improved.It is concluded that the robust optimization method proposed in this paper is a reasonable way to optimize the mixed-flow pump,and provides references for optimization problems of other fluid machinery.展开更多
Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach wa...Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.展开更多
An optimized methodology to design a more robust torpedo shell is proposed. The method has taken into account reliability requirements and controllable and uncontrollable factors such as geometry, load, material prope...An optimized methodology to design a more robust torpedo shell is proposed. The method has taken into account reliability requirements and controllable and uncontrollable factors such as geometry, load, material properties, manufacturing processes, installation, etc. as well as human and environmental factors. The result is a more realistic shell design. Our reliability optimization design model was developed based on sensitivity analysis. Details of the design model are given in this paper. An example of a torpedo shell design based on this model is given and demonstrates that the method produces designs that are more effective and reliable than traditional torpedo shell designs. This method can be used for other torpedo system designs.展开更多
This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We...This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We aim to maximize the throughput overall GTs by jointly optimizing the UAVs’trajectory,the GTs’scheduling and power allocation.Unlike most prior studies,we consider the UAVs’turning and climbing angle constraints,the UAVs’three-dimensional(3D)trajectory constraints,minimum UAV-to-UAV(U2U)distance constraint,and the GTs’transmit power requirements.However,the formulated problem is a mixed-integer non-convex problem and is intractable to work it out with conventional optimization methods.To tackle this difficulty,we propose an efficient robust iterative algorithm to decompose the original problem be three sub-problems and acquire the suboptimal solution via utilizing the block coordinate descent(BCD)method,successive convex approximation(SCA)technique,and S-procedure.Extensive simulation results show that our proposed robust iterative algorithm offers a substantial gain in the system performance compared with the benchmark algorithms.展开更多
基金Supported by the Science and Technology Support Key Project of 12th Five-Year of China(2011BAD20B00-4)~~
文摘The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.
文摘Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission scheme for an AirCompbased FL system with imperfect channel state information(CSI)is proposed.To model CSI uncertainty,an expectation-based error model is utilized.The main objective is to maximize the number of selected devices that meet mean-squared error(MSE)requirements for model broadcast and model aggregation.The problem is formulated as a combinatorial optimization problem and is solved in two steps.First,the priority order of devices is determined by a sparsity-inducing procedure.Then,a feasibility detection scheme is used to select the maximum number of devices to guarantee that the MSE requirements are met.An alternating optimization(AO)scheme is used to transform the resulting nonconvex problem into two convex subproblems.Numerical results illustrate the effectiveness and robustness of the proposed scheme.
基金National Natural Science Foundation of China(51609107)Open Subject of Provincial and Ministerial Discipline Platform of Xihua University(szjj2018-123)。
文摘To increase the robustness of the optimization solutions of the mixed-flow pump,the impeller was firstly indirectly parameterized based on the 2D blade design theory.Secondly,the robustness of the optimization solution was mathematically defined,and then calculated by Monte Carlo sampling method.Thirdly,the optimization on the mixed-flow pump′s impeller was decomposed into the optimal and robust sub-optimization problems,to maximize the pump head and efficiency and minimize the fluctuation degree of them under varying working conditions at the same time.Fourthly,using response surface model,a surrogate model was established between the optimization objectives and control variables of the shape of the impeller.Finally,based on a multi-objective genetic optimization algorithm,a two-loop iterative optimization process was designed to find the optimal solution with good robustness.Comparing the original and optimized pump,it is found that the internal flow field of the optimized pump has been improved under various operating conditions,the hydraulic performance has been improved consequently,and the range of high efficient zone has also been widened.Besides,with the changing of working conditions,the change trend of the hydraulic performance of the optimized pump becomes gentler,the flow field distribution is more uniform,and the influence degree of the varia-tion of working conditions decreases,and the operating stability of the pump is improved.It is concluded that the robust optimization method proposed in this paper is a reasonable way to optimize the mixed-flow pump,and provides references for optimization problems of other fluid machinery.
文摘Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.
基金the National Defense Basic Research Project Foundation under Grant No. B2720061149
文摘An optimized methodology to design a more robust torpedo shell is proposed. The method has taken into account reliability requirements and controllable and uncontrollable factors such as geometry, load, material properties, manufacturing processes, installation, etc. as well as human and environmental factors. The result is a more realistic shell design. Our reliability optimization design model was developed based on sensitivity analysis. Details of the design model are given in this paper. An example of a torpedo shell design based on this model is given and demonstrates that the method produces designs that are more effective and reliable than traditional torpedo shell designs. This method can be used for other torpedo system designs.
文摘This paper studies a multi-unmanned aerial vehicle(UAV)enabled wireless communication system,where multiple UAVs are employed to communicate with a group of ground terminals(GTs)in the presence of potential jammers.We aim to maximize the throughput overall GTs by jointly optimizing the UAVs’trajectory,the GTs’scheduling and power allocation.Unlike most prior studies,we consider the UAVs’turning and climbing angle constraints,the UAVs’three-dimensional(3D)trajectory constraints,minimum UAV-to-UAV(U2U)distance constraint,and the GTs’transmit power requirements.However,the formulated problem is a mixed-integer non-convex problem and is intractable to work it out with conventional optimization methods.To tackle this difficulty,we propose an efficient robust iterative algorithm to decompose the original problem be three sub-problems and acquire the suboptimal solution via utilizing the block coordinate descent(BCD)method,successive convex approximation(SCA)technique,and S-procedure.Extensive simulation results show that our proposed robust iterative algorithm offers a substantial gain in the system performance compared with the benchmark algorithms.
