As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting ...As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting surface(IRS)is introduced into its signal propagation path.Consequently,an IRSaided PSR is concerned for a point-to-point(P2P)data link,where both the single-antenna and multiantenna deployments on the receiver are discussed.We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beamforming of IRS and the splitting ratio of PSR,either in single-antenna or multi-antenna case.However,owing to the coupling of multiple variables,the optimization problems are non-convex and challenging,especially in the later multi-antenna case.The proposed alternating-approximating algorithm(A-A),aided by semi-definite relaxation(SDR)and successive convex approximation(SCA)methods,etc.,successfully overcomes these challenges.We compare the IRS-aided PSR system that optimized by our proposed algorithm to the systems without IRS or PSR,and the systems without joint optimization.The simulation results show that our proposal has a better performance.展开更多
Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article...Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article specifically considers the UAV-enabled orthogonal frequency division multiple access(OFDMA)wireless communication network.Consid-ering a practical scenario,a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility,limited total resource and backhaul link rate has been formulated,which aims to maximize the minimum achievable average rate of the users.To tackle the coupling and non-convexity of the proposed problem,an efficient opti-mization algorithm has been proposed based on alter-nating optimization,successive convex approximation and introducing slack variable techniques.Simulation results illustrate that the proposed optimization algo-rithm can effectively improve the system performance.Also,the numerical results unveil that joint optimiza-tion is superior to baseline schemes.展开更多
The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backsca...The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.展开更多
Quadruped robots with body joints exhibit enhanced mobility,however,in outdoor environments,the energy that the robot can carry is limited,necessitating optimization of energy consumption to accomplish more tasks with...Quadruped robots with body joints exhibit enhanced mobility,however,in outdoor environments,the energy that the robot can carry is limited,necessitating optimization of energy consumption to accomplish more tasks within these constraints.Inspired by quadruped animals,this paper proposes an energy-saving strategy for a body joint quadruped robot based on Central Pattern Generator(CPG)with multi-sensor fusion bio-reflexes.First,an energy consumption model for the robot is established,and energy characteristic tests are conducted under different gait parameters.Based on these energy characteristics,optimal energy-efficient gait parameters are determined for various environmental conditions.Second,biological reflex mechanisms are studied,and a motion control model based on multi-sensor fusion biological reflexes is established using CPG as the foundation.By integrating the reflex model and gait parameters,real-time adaptive adjustments to the robot’s motion gait are achieved on complex terrains,reducing energy loss caused by terrain disturbances.Finally,a prototype of the body joint quadruped robot is built for experimental verification.Simulation and experimental results demonstrate that the proposed algorithm effectively reduces the robot’s Cost of Transport(COT)and significantly improves energy efficiency.The related research results can provide a useful reference for the research on energy efficiency of quadruped robots on complex terrain.展开更多
Refill friction stir spot welding process is difficultly optimized by accurate modeling because of the high-order functional relationship between welding parameters and joint strength.A database of the welding process...Refill friction stir spot welding process is difficultly optimized by accurate modeling because of the high-order functional relationship between welding parameters and joint strength.A database of the welding process was first established with 6061-T6 aluminum alloy and DP780 galvanized steel as base materials.This dataset was then optimized using a backpropagation neural network.Analyses and mining of the experimental data confirmed the multidimensional mapping relationship between welding parameters and joint strength.Subsequently,intelligent optimization of the welding process and prediction of joint strength were achieved.At the predicted welding parameter(plunging rotation speedω1=1733 r/min,refilling rotation speedω_(2)=1266 r/min,plunging depth p=1.9 mm,and welding speed v=0.5 mm/s),the tensile shear fracture load of the joint reached a maximum value of 10,172 N,while the experimental result was 9980 N,with an error of 1.92%.Furthermore,the correlation of welding parameters-microstructure-joint strength was established.展开更多
To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track ...To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track was derived based on the principle of stationary potential energy.Considering interlayer evolution and structural crack propagation,an optimized joint repair model for the track was established and validated.Subsequently,the impact of joint repair on track damage and arch stability under extreme temperatures was studied,and a comprehensive evaluation of the feasibility of joint repair and the evolution of damage after repair was conducted.The results show that after the joint repair,the temperature rise of the initial damage of the track structure can be increased by 11℃.Under the most unfavorable heating load with a superimposed temperature gradient,the maximum stiffness degradation index SDEG in the track structure is reduced by about 81.16%following joint repair.The joint repair process could effectively reduce the deformation of the slab arching under high temperatures,resulting in a reduction of 93.96%in upward arching deformation.After repair,with the damage to interfacing shear strength,the track arch increases by 2.616 mm.展开更多
This paper presents an extended topology optimization approach considering joint load constraints with geo-metrical nonlinearity in design of assembled structures.The geometrical nonlinearity is firstly included to re...This paper presents an extended topology optimization approach considering joint load constraints with geo-metrical nonlinearity in design of assembled structures.The geometrical nonlinearity is firstly included to reflect the structural response and the joint load distribution under large deformation.To avoid a failure of fastener joints,topology optimization is then carried out to minimize the structural end compliance in the equilibrium state while controlling joint loads intensities over fasteners.During nonlinear analysis and optimization,a novel implementation of adjoint vector sensitivity analysis along with super element condensation is introduced to address numerical instability issues.The degrees of freedom of weak regions are condensed so that their influences are excluded from the iterative Newton-Raphson(NR)solution.Numerical examples are presented to validate the efficiency and robustness of the proposed method.The effects of joint load constraints and geometrical nonlinearity are highlighted by comparing numerical optimization results.展开更多
Despite significant improvements over the past several decades in diagnosis,treatment and prevention of periprosthetic joint infection(PJI),it still remains a major challenge following total joint arthroplasty.Given t...Despite significant improvements over the past several decades in diagnosis,treatment and prevention of periprosthetic joint infection(PJI),it still remains a major challenge following total joint arthroplasty.Given the devastating nature and accelerated incidence of PJI,prevention is the most important strategy to deal with this challenging problem and should start from identifying risk factors.Understanding and well-organized optimization of these risk factors in individuals before elective arthroplasty are essential to the ultimate success in reducing the incidence of PJI.Even though some risk factors such as demographic characteristics are seldom changeable,they allow more accurate expectation regarding individual risks of PJI and thus,make proper counseling for shared preoperative decision-making possible.Others that increase the risk of PJI,but are potentially modifiable should be optimized prior to elective arthroplasty.Although remarkable advances have been achieved in past decades,many questions regarding standardized practice to prevent this catastrophic complication remain unanswered.The current study provide a comprehensive knowledge regarding risk factors based on general principles to control surgical siteinfection by the review of current literature and also share own practice at our institution to provide practical and better understandings.展开更多
With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircr...With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.展开更多
In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.Howev...To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.展开更多
The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The tr...The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.展开更多
This work focuses on an unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) system based on device-to-device(D2D) communication. In this system, the UAV exhibits caching,computing and relaying capabilities...This work focuses on an unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) system based on device-to-device(D2D) communication. In this system, the UAV exhibits caching,computing and relaying capabilities to periodically provide specific service to cellular users and D2D receiver nodes in the appointed time slot. Besides, the D2D transmitter can provide additional caching services to D2D receiver to reduce the pressure of the UAV. Note that communication between multi-type nodes is mutually restricted and different links share spectrum resources. To achieve an improved balance between different types of node, we aim to maximize the overall energy efficiency while satisfying the quality-of-service requirements of the cellular nodes.To address this problem, we propose an alternating iteration algorithm to jointly optimize the scheduling strategies of the user, transmitting power of the UAV and D2D-TX nodes, and UAV trajectory. The successive convex approximation, penalty function, and Dinkelbach method are employed to transform the original problem into a group of solvable subproblems and the convergence of the method is proved. Simulation results show that the proposed scheme performs better than other benchmark algorithms, particularly in terms of balancing the tradeoff between minimizing UAV energy consumption and maximizing throughput.展开更多
In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable sola...In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable solar array model consists of a rigid main-body,two panels and four key mechanisms,containing torsion spring mechanism,closed cable loop mechanism,latch mechanism and attitude adjustment mechanism.Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation,respectively.The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model.The latch time,stabilization time,maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works.To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties,a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints.Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected.Besides,increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system.That may provide some references for optimization design of deployable space mechanisms considering clearance joints.展开更多
To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network...To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.展开更多
Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to e...Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.展开更多
Treatment of bone tumors in the mandible often involves extensive excavation of affected bone, followed by mandibular reconstruction. Prosthetic implants may be needed to restore jaw functionality. The challenges of m...Treatment of bone tumors in the mandible often involves extensive excavation of affected bone, followed by mandibular reconstruction. Prosthetic implants may be needed to restore jaw functionality. The challenges of making prosthetic bone implants include stress shielding and extending the mechanical life of the implant. We have developed a design algorithm to improve the efficiency of prosthesis design. A finite element model of the patient case is constructed from a computer tomography scan, and the computer implements topology optimization techniques to design the prosthesis with limited stress shielding affected by highly biomechanical compatibility. Topology optimization facilitates the design of low weight structures by automatically introducing holes into the structure. This is governed by engineering predetermined constraints to meet certain job specifications. Such a design will be tested for fatigue life before it is ready to be manufactured and used. Topology optimization can be performed as a design process to achieve a final design that takes stress shielding into consideration. The problem of stress shielding is solved by matching the stiffness of the orthopedic implant to the original bone that is being replaced. The material we used was titanium alloy (Ti-6Al-7Nb). Volume fraction of the orthodox implant was used (0.2872 for the studied case) as volume constraints. Compliance of the bulk bone was set as a further constraint to match the stiffness of the bone with the designed structure. Our results show a good life expectancy for the designed parts, with 12% higher life expectancy for stress-based topology optimization than for compliance-based topology optimization.展开更多
In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,th...In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.展开更多
The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces ...The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.展开更多
Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective...Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.展开更多
基金supported by National Key R&D Program of China with Grant number 2019YFB1803400in part by Sichuan Science and Technology Program under Grant 2024NSFSC0472。
文摘As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting surface(IRS)is introduced into its signal propagation path.Consequently,an IRSaided PSR is concerned for a point-to-point(P2P)data link,where both the single-antenna and multiantenna deployments on the receiver are discussed.We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beamforming of IRS and the splitting ratio of PSR,either in single-antenna or multi-antenna case.However,owing to the coupling of multiple variables,the optimization problems are non-convex and challenging,especially in the later multi-antenna case.The proposed alternating-approximating algorithm(A-A),aided by semi-definite relaxation(SDR)and successive convex approximation(SCA)methods,etc.,successfully overcomes these challenges.We compare the IRS-aided PSR system that optimized by our proposed algorithm to the systems without IRS or PSR,and the systems without joint optimization.The simulation results show that our proposal has a better performance.
基金supported by Project funded in part by China Postdoctoral Science Foundation(No.2021MD703980)in part by the National Natural Science Foundation of China(No.61901502).
文摘Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article specifically considers the UAV-enabled orthogonal frequency division multiple access(OFDMA)wireless communication network.Consid-ering a practical scenario,a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility,limited total resource and backhaul link rate has been formulated,which aims to maximize the minimum achievable average rate of the users.To tackle the coupling and non-convexity of the proposed problem,an efficient opti-mization algorithm has been proposed based on alter-nating optimization,successive convex approximation and introducing slack variable techniques.Simulation results illustrate that the proposed optimization algo-rithm can effectively improve the system performance.Also,the numerical results unveil that joint optimiza-tion is superior to baseline schemes.
文摘The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.
基金supported by the National Natural Science Foundation of China(Grant no.52075488)the Natural Science Foundation of Zhejiang Province(LY20E050023).
文摘Quadruped robots with body joints exhibit enhanced mobility,however,in outdoor environments,the energy that the robot can carry is limited,necessitating optimization of energy consumption to accomplish more tasks within these constraints.Inspired by quadruped animals,this paper proposes an energy-saving strategy for a body joint quadruped robot based on Central Pattern Generator(CPG)with multi-sensor fusion bio-reflexes.First,an energy consumption model for the robot is established,and energy characteristic tests are conducted under different gait parameters.Based on these energy characteristics,optimal energy-efficient gait parameters are determined for various environmental conditions.Second,biological reflex mechanisms are studied,and a motion control model based on multi-sensor fusion biological reflexes is established using CPG as the foundation.By integrating the reflex model and gait parameters,real-time adaptive adjustments to the robot’s motion gait are achieved on complex terrains,reducing energy loss caused by terrain disturbances.Finally,a prototype of the body joint quadruped robot is built for experimental verification.Simulation and experimental results demonstrate that the proposed algorithm effectively reduces the robot’s Cost of Transport(COT)and significantly improves energy efficiency.The related research results can provide a useful reference for the research on energy efficiency of quadruped robots on complex terrain.
基金the financial supports provided by the National Key Research and Development Program of China(2023YFE0201500)the National Natural Science Foundation of China(52375315)+2 种基金the Key Talent Plan Project of Guangdong Province(2023TQ07C702)the Research and Development Program in Key Areas of Dongguan(20201200300122)the GDAS’Project of Science and Technology Development(2022GDASZH-2022010203).
文摘Refill friction stir spot welding process is difficultly optimized by accurate modeling because of the high-order functional relationship between welding parameters and joint strength.A database of the welding process was first established with 6061-T6 aluminum alloy and DP780 galvanized steel as base materials.This dataset was then optimized using a backpropagation neural network.Analyses and mining of the experimental data confirmed the multidimensional mapping relationship between welding parameters and joint strength.Subsequently,intelligent optimization of the welding process and prediction of joint strength were achieved.At the predicted welding parameter(plunging rotation speedω1=1733 r/min,refilling rotation speedω_(2)=1266 r/min,plunging depth p=1.9 mm,and welding speed v=0.5 mm/s),the tensile shear fracture load of the joint reached a maximum value of 10,172 N,while the experimental result was 9980 N,with an error of 1.92%.Furthermore,the correlation of welding parameters-microstructure-joint strength was established.
基金Project(K2022G038)supported by the Science Technology Research and Development Program of China State Railway Group Co.,LtdProject(52178405)supported by the National Natural Science Foundation of China。
文摘To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track was derived based on the principle of stationary potential energy.Considering interlayer evolution and structural crack propagation,an optimized joint repair model for the track was established and validated.Subsequently,the impact of joint repair on track damage and arch stability under extreme temperatures was studied,and a comprehensive evaluation of the feasibility of joint repair and the evolution of damage after repair was conducted.The results show that after the joint repair,the temperature rise of the initial damage of the track structure can be increased by 11℃.Under the most unfavorable heating load with a superimposed temperature gradient,the maximum stiffness degradation index SDEG in the track structure is reduced by about 81.16%following joint repair.The joint repair process could effectively reduce the deformation of the slab arching under high temperatures,resulting in a reduction of 93.96%in upward arching deformation.After repair,with the damage to interfacing shear strength,the track arch increases by 2.616 mm.
基金co-supported by National Key Research and Development Program(No.2017YFB1102800)NSFC for Excellent Young Scholars(No.11722219)Key Project of NSFC(Nos.51790171,5171101743,51735005,11620101002,and 11432011).
文摘This paper presents an extended topology optimization approach considering joint load constraints with geo-metrical nonlinearity in design of assembled structures.The geometrical nonlinearity is firstly included to reflect the structural response and the joint load distribution under large deformation.To avoid a failure of fastener joints,topology optimization is then carried out to minimize the structural end compliance in the equilibrium state while controlling joint loads intensities over fasteners.During nonlinear analysis and optimization,a novel implementation of adjoint vector sensitivity analysis along with super element condensation is introduced to address numerical instability issues.The degrees of freedom of weak regions are condensed so that their influences are excluded from the iterative Newton-Raphson(NR)solution.Numerical examples are presented to validate the efficiency and robustness of the proposed method.The effects of joint load constraints and geometrical nonlinearity are highlighted by comparing numerical optimization results.
基金Supported by The grant of Research Institute of Medical Science,Catholic University of Daegu(2011)
文摘Despite significant improvements over the past several decades in diagnosis,treatment and prevention of periprosthetic joint infection(PJI),it still remains a major challenge following total joint arthroplasty.Given the devastating nature and accelerated incidence of PJI,prevention is the most important strategy to deal with this challenging problem and should start from identifying risk factors.Understanding and well-organized optimization of these risk factors in individuals before elective arthroplasty are essential to the ultimate success in reducing the incidence of PJI.Even though some risk factors such as demographic characteristics are seldom changeable,they allow more accurate expectation regarding individual risks of PJI and thus,make proper counseling for shared preoperative decision-making possible.Others that increase the risk of PJI,but are potentially modifiable should be optimized prior to elective arthroplasty.Although remarkable advances have been achieved in past decades,many questions regarding standardized practice to prevent this catastrophic complication remain unanswered.The current study provide a comprehensive knowledge regarding risk factors based on general principles to control surgical siteinfection by the review of current literature and also share own practice at our institution to provide practical and better understandings.
基金supported by the Fundamental Research Funds for the Central Universities(NS2015072)
文摘With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
基金the National Natural Science Foundation of China(NO.51405229)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20151470 and BK20130796)
文摘To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.
基金Project(61171133) supported by the National Natural Science Foundation of ChinaProject(11JJ1010) supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,China
文摘The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.
基金the supports from the National Natural Science Foundation of China (61571156)Basic Research Project of Shenzhen (JCYJ20170413110004682 and JCYJ20150403161923521)。
文摘This work focuses on an unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) system based on device-to-device(D2D) communication. In this system, the UAV exhibits caching,computing and relaying capabilities to periodically provide specific service to cellular users and D2D receiver nodes in the appointed time slot. Besides, the D2D transmitter can provide additional caching services to D2D receiver to reduce the pressure of the UAV. Note that communication between multi-type nodes is mutually restricted and different links share spectrum resources. To achieve an improved balance between different types of node, we aim to maximize the overall energy efficiency while satisfying the quality-of-service requirements of the cellular nodes.To address this problem, we propose an alternating iteration algorithm to jointly optimize the scheduling strategies of the user, transmitting power of the UAV and D2D-TX nodes, and UAV trajectory. The successive convex approximation, penalty function, and Dinkelbach method are employed to transform the original problem into a group of solvable subproblems and the convergence of the method is proved. Simulation results show that the proposed scheme performs better than other benchmark algorithms, particularly in terms of balancing the tradeoff between minimizing UAV energy consumption and maximizing throughput.
基金supported by the National Natural Science Foundation of China(No.U1637207)Beijing Natural Science Foundation of China(No.1204040)。
文摘In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable solar array model consists of a rigid main-body,two panels and four key mechanisms,containing torsion spring mechanism,closed cable loop mechanism,latch mechanism and attitude adjustment mechanism.Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation,respectively.The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model.The latch time,stabilization time,maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works.To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties,a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints.Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected.Besides,increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system.That may provide some references for optimization design of deployable space mechanisms considering clearance joints.
文摘To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.
基金Supported by National Key Research and Development Program of China (Grant Nos.2022YFB4703000,2019YFB1309900)。
文摘Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.
文摘Treatment of bone tumors in the mandible often involves extensive excavation of affected bone, followed by mandibular reconstruction. Prosthetic implants may be needed to restore jaw functionality. The challenges of making prosthetic bone implants include stress shielding and extending the mechanical life of the implant. We have developed a design algorithm to improve the efficiency of prosthesis design. A finite element model of the patient case is constructed from a computer tomography scan, and the computer implements topology optimization techniques to design the prosthesis with limited stress shielding affected by highly biomechanical compatibility. Topology optimization facilitates the design of low weight structures by automatically introducing holes into the structure. This is governed by engineering predetermined constraints to meet certain job specifications. Such a design will be tested for fatigue life before it is ready to be manufactured and used. Topology optimization can be performed as a design process to achieve a final design that takes stress shielding into consideration. The problem of stress shielding is solved by matching the stiffness of the orthopedic implant to the original bone that is being replaced. The material we used was titanium alloy (Ti-6Al-7Nb). Volume fraction of the orthodox implant was used (0.2872 for the studied case) as volume constraints. Compliance of the bulk bone was set as a further constraint to match the stiffness of the bone with the designed structure. Our results show a good life expectancy for the designed parts, with 12% higher life expectancy for stress-based topology optimization than for compliance-based topology optimization.
基金supported by the National Key R&D Program of China under Grant 2019YFB1803400partly by National Natural Science Foundation of China under Grant 62071394.
文摘In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.
基金The work was supported by the Science Challenge Project(Grant No.TZ2018007)The authors also thank the National Natural Science Foundation of China(Grant Nos.11872059,11702279)National Defense Technology Foundation of China(Grant No.JSUS2018212C)for providing the financial support for this project.
文摘The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.
文摘Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.
