The emergence of adaptive facades offers a new approach for buildings to enhance their resilience against external weather conditions while responding to occupants’demands,thereby improving both indoor environmental ...The emergence of adaptive facades offers a new approach for buildings to enhance their resilience against external weather conditions while responding to occupants’demands,thereby improving both indoor environmental quality and energy performance.Appropriate control methods are crucial to achieving these purposes.However,most existing studies for automatic control of blinds have focused on visual comfort,leaving potential for further energy savings by reducing cooling and artificial lighting demands.Additionally,current optimization methods for slat angles are mostly simplified as a discrete process,neglecting the impact of thermal mass in building envelopes.Therefore,this paper aims to explore the energy reduction potential of window blinds by developing an iterative optimization method for devising hourly adaptive control strategies.To this end,a co-simulation platform between EnergyPlus and Python was established for the optimization and a case study in a subtropical city was conducted.The proposed strategies effectively balanced lighting and cooling demands to achieve an overall energy reduction of 7.3%–12.5%compared to reference cases while also ensuring visual comfort by mitigating glare risk and excessive daylight.These advantages were also compared with several simpler control scenarios,with analyses tailored to various glazing types and orientations.Furthermore,the optimal window configurations with blind control strategies for different orientations were determined.The findings also indicated that glass properties markedly impact the performance of control strategies,underscoring the necessity of holistically considering shading components and glazing types in the optimization to achieve optimal performance.展开更多
Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural ...Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.展开更多
A general(abstract)scheme of iterative improvement and optimization on the base of extension,localization principles which would help to generate new concrete methods and algorithms for new problems is proposed.Appli...A general(abstract)scheme of iterative improvement and optimization on the base of extension,localization principles which would help to generate new concrete methods and algorithms for new problems is proposed.Application to optimal control problems for continuous systems is considered.Visual example is given.展开更多
An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVD...An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.展开更多
In cognitive radio(CR)systems,efficient spectrum sensing ensures the secondary user(SU)to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of t...In cognitive radio(CR)systems,efficient spectrum sensing ensures the secondary user(SU)to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of transmission strategy.However,in practice,due to non-zero probabilities of miss detection and false alarm,the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user(PU).In this paper,using energy detection,we maximize the total throughput of SUs by jointly optimizing the detection threshold and transmission strategy in multiband CR systems.A set of iteration based algorithms are proposed to solve this mix-integer programming problem,which show better performance compared with uniform detection threshold selection algorithm suggested by IEEE 802.22 standard.展开更多
High-resolution seeing through complex scattering media such as turbid water,biological tissues,and mist is a significant challenge because the strong scattering scrambles the light paths and forms the scattering wall...High-resolution seeing through complex scattering media such as turbid water,biological tissues,and mist is a significant challenge because the strong scattering scrambles the light paths and forms the scattering wall.We propose an active polarized iterative optimization approach for high-resolution imaging through complex scattering media.By acquiring a series of sub-polarized images,we can capture the diverse pattern-illuminated images with various high-frequency component information caused by the Brownian motion of complex scattering materials,which are processed using the common-mode rejection of polarization characteristics to extract target information from scattering medium information.Following that,our computational reconstruction technique employs an iterative optimization algorithm that commences with patternilluminated Fourier ptychography for reconstructing the high-resolution scene.It is extremely important that our approach for high-resolution imaging through complex scattering media is not limited by priori information and optical memory effect.The proposed approach is suitable for not only dynamic but also static scattering media,which may find applications in the biomedicine field,such as skin abnormalities,non-invasive blood flow,and superficial tumors.展开更多
To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.Th...To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.The eavesdropping on the UR is interfered by a source-based jamming strategy.Under the constraints of unit modulus and total power,the RIS phase shift,the power allocation between the confidential signal and the jamming signal,and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate.The complex multivariable coupling problem is decomposed into three sub-problems,and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation.Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme,the random phase shift scheme,and the no-RIS scheme.展开更多
In the present paper, based on the theory of dynamic boundary integral equation, an optimization method for crack identification is set up in the Laplace frequency space, where the direct problem is solved by the auth...In the present paper, based on the theory of dynamic boundary integral equation, an optimization method for crack identification is set up in the Laplace frequency space, where the direct problem is solved by the author's new type boundary integral equations and a method for choosing the high sensitive frequency region is proposed. The results show that the method proposed is successful in using the information of boundary elastic wave and overcoming the ill-posed difficulties on solution, and helpful to improve the identification precision.展开更多
In the stability framework of model predictive control(MPC),the size of the stabilizable set(also known as the region of attraction)is dependent on the terminal constraint region.This article aims to investigate the o...In the stability framework of model predictive control(MPC),the size of the stabilizable set(also known as the region of attraction)is dependent on the terminal constraint region.This article aims to investigate the optimization of the terminal region for predictive control of a class of systems with multiplicative uncertainty,aiming to expand the attraction region in MPC.By utilizing a coordinate transformation,we initially develop a structured design for terminal ingredients while considering uncertainties in parameters.Subsequently,we propose novel methods to convert the original nonlinear problem into a linear matrix inequality(LMI)problem with minimal conservatism in the formulation.We propose an iterative learning optimization approach to compute the polytopic terminal region,and its incremental volume is theoretically proven.The efectiveness of the proposed approaches is demonstrated using a benchmark academic example and vehicle lateral dynamics.Through real-time simulation experiments,we demonstrate that the proposed approach can enlarge the domain of attraction as well as reduce the computational complexity of robust MPC systems under parameter uncertainty.展开更多
In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is ...In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is powerful for the problems characterized by small samples, nonlinearity, high dimension and local minima, support vector regression models are developed for the optimal control of batch processes where end-point properties are required. The model parameters are selected within the Bayesian evidence framework. Based on the model, an iterative method is used to exploit the repetitive nature of batch processes to determine the optimal operating policy. Numerical simulation shows that the iterative optimal control can improve the process performance through iterations.展开更多
This study develops an optimized finite difference iterative （OFDI） scheme for the two-dimensional （2D） viscoelastic wave equation. The OFDI scheme is obtained using a proper orthogonal decomposition （POD） metho...This study develops an optimized finite difference iterative （OFDI） scheme for the two-dimensional （2D） viscoelastic wave equation. The OFDI scheme is obtained using a proper orthogonal decomposition （POD） method. It has sufficiently high accuracy with very few unknowns for the 2D viscoelastic wave equation. Existence, stability, and convergence of the OFDI solutions are analyzed. Numerical simulations verify efficiency and feasibility of the proposed scheme.展开更多
RSs(Radar Systems)identify and trace targets and are commonly employed in applications like air traffic control and remote sensing.They are necessary for monitoring precise target trajectories.Estimations of RSs are n...RSs(Radar Systems)identify and trace targets and are commonly employed in applications like air traffic control and remote sensing.They are necessary for monitoring precise target trajectories.Estimations of RSs are non-linear as the parameters TDEs(time delay Estimations)and Doppler shifts are computed on receipt of echoes where EKFs(Extended Kalman Filters)and UKFs(Unscented Kalman Filters)have not been examined for computations.RSs,certain times result in poor accuracies and SNRs(low signal to noise ratios)especially,while encountering complicated environments.This work proposes IUKFs(Iterated UKFs)to track onlinefilter performances while using optimization techniques to enhance outcomes.The use of cost functions can assist state corrections while lowering costs.A new parameter is optimized using MCEHOs(Mutation Chaotic Elephant Herding Optimizations)by linearly approximating system non-linearity where OIUKFs(Optimized Iterative UKFs)predict a target's unknown parameters.To obtain optimal solutions theoretically,OIUKFs take less iteration,resulting in shorter execution times.The proposed OIUKFs provide numerical approximations which are derivative-free implementations.Simulation evaluation results with estimators show better performances in terms of reduced NMSEs(Normalized Mean Square Errors),RMSEs(Root Mean Squared Errors),SNRs,variances,and better accuracies than current approaches.展开更多
This paper describes a new design of the neutral beam manifold based on a more optimized support system.A proposed alternative scheme has presented to replace the former complex manifold supports and internal pipe sup...This paper describes a new design of the neutral beam manifold based on a more optimized support system.A proposed alternative scheme has presented to replace the former complex manifold supports and internal pipe supports in the final design phase.Both the structural reliability and feasibility were confirmed with detailed analyses.Comparative analyses between two typical types of manifold support scheme were performed.All relevant results of mechanical analyses for typical operation scenarios and fault conditions are presented.Future optimization activities are described,which will give useful information for a refined setting of components in the next phase.展开更多
This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates ...This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.展开更多
An iterative optimization strategy is proposed and applied to the steady state optimizing control of the bio-dissimilation process of glycerol to 1,3-propanediol in the presence of model-plant mismatch and input const...An iterative optimization strategy is proposed and applied to the steady state optimizing control of the bio-dissimilation process of glycerol to 1,3-propanediol in the presence of model-plant mismatch and input constraints. The scheme is based on the Augmented Integrated System Optimization and Parameter Estimation （AI- SOPE） technique, but a linearization of some performance function in the modified model-based optimization problem of AISOPE is introduced to overcome the difficulty of determining an appropriate penalty parameter. When carrying out the iterative optimization, the penalty coefficient is set to a larger value at the current iteration than at the previous iteration, which can promote the evolution rate of the iterative optimization. Simulation studies illustrate the potential ofthe approach presented for the optimizing control of the bioTdissimilation process of glycerol to 1,3-propanediol. The effects of measurement noise, measured and unmeasured disturbances on the proposed algorithm are also investigated.展开更多
Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades.The key challenges for achieving this goal are carbon emission trading and elec...Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades.The key challenges for achieving this goal are carbon emission trading and electricity sector regulation,which are also the major components of the carbon and electricity markets,respectively.In this paper,a joint electricity and carbon market model is proposed to investigate the relationships between electricity price,carbon price,and electricity generation capacity,thereby identifying pathways toward a renewable energy transition under the transactional energy interconnection framework.The proposed model is a dynamically iterative optimization model consisting of upper-level and lower-level models.The upper-level model optimizes power generation and obtains the electricity price,which drives the lower-level model to update the carbon price and electricity generation capacity.The proposed model is verified using the Northeast Asia power grid.The results show that increasing carbon price will result in increased electricity price,along with further increases in renewable energy generation capacity in the following period.This increase in renewable energy generation will reduce reliance on carbon-emitting energy sources,and hence the carbon price will decline.Moreover,the interconnection among zones in the Northeast Asia power grid will enable reasonable allocation of zonal power generation.Carbon capture and storage (CCS) will be an effective technology to reduce the carbon emissions and further realize the emission reduction targets in 2030-2050.It eases the stress of realizing the energy transition because of the less urgency to install additional renewable energy capacity.展开更多
Fluorescence lifetime imaging can reveal the high-resolution structure of various biophysical and chemical parameters in a microenvironment quantitatively.However,the depth of imaging is generally limited to hundreds ...Fluorescence lifetime imaging can reveal the high-resolution structure of various biophysical and chemical parameters in a microenvironment quantitatively.However,the depth of imaging is generally limited to hundreds of micrometers due to aberration and light scattering in biological tissues.This paper introduces an iterative multi-photon adaptive compensation technique(IMPACT)into a two-photon fluorescence lifetime microscopy system to successfully overcome aberrations and multiple scattering problems in deep tissues.It shows that 400 correction modes can be achieved within 5 min,which was mainly limited by the frame rate of a spatial light modulator.This system was used for high-resolution imaging of mice brain tissue and live zebrafish,further verifying its superior performance in imaging quality and photon accumulation speed.展开更多
Background Aiming at free-view exploration of complicated scenes,this paper presents a method for interpolating views among multi RGB cameras.Methods In this study,we combine the idea of cost volume,which represent 3 ...Background Aiming at free-view exploration of complicated scenes,this paper presents a method for interpolating views among multi RGB cameras.Methods In this study,we combine the idea of cost volume,which represent 3 D information,and 2 D semantic segmentation of the scene,to accomplish view synthesis of complicated scenes.We use the idea of cost volume to estimate the depth and confidence map of the scene,and use a multi-layer representation and resolution of the data to optimize the view synthesis of the main object.Results/Conclusions By applying different treatment methods on different layers of the volume,we can handle complicated scenes containing multiple persons and plentiful occlusions.We also propose the view-interpolation→multi-view reconstruction→view interpolation pipeline to iteratively optimize the result.We test our method on varying data of multi-view scenes and generate decent results.展开更多
The quality prediction of tube hollow model based on the variance staged multiway partial least square (MPLS) method was proposed.The key aspects of staged decomposition of the productive data,calculation of the varia...The quality prediction of tube hollow model based on the variance staged multiway partial least square (MPLS) method was proposed.The key aspects of staged decomposition of the productive data,calculation of the variance value,modeling,and on-lined prediction in the variance-staged MPLS method were introduced.Based on the model,iterative optimal control method was used for quality control of tube hollow.The experimental results show that the obvious benefits of this method are low maintenance cost,good real time function,high reliability precision,and practical application to on-line prediction and optimization on the quality of tube hollow.展开更多
This paper proposes a sensitivity analysis method for engineering parameters using interval analyses.This method substantially extends the application of interval analysis method.In this scheme,parameter intervals and...This paper proposes a sensitivity analysis method for engineering parameters using interval analyses.This method substantially extends the application of interval analysis method.In this scheme,parameter intervals and decision-making target intervals are determined using the interval analysis method.As an example,an inverse analysis method for uncertainty is presented.The intervals of unknown parameters can be obtained by sampling measured data.Even for limited measured data,robust results can also be obtained with the inverse analysis method,which can be intuitively evaluated by the uncertainty expressed in terms of an interval.For complex nonlinear problems,an iteratively optimized inverse analysis model is proposed.In a given set of loose parameter intervals,all the unknown parameter intervals that satisfy the measured information can be obtained by an iteratively optimized inverse analysis model.The influences of measured precisions and the number of parameters on the results of the inverse analysis are evaluated.Finally,the uniqueness of the interval inverse analysis method is discussed.展开更多
基金supported by the National Key Research and Development Project of China(No.2019YFE0124500).
文摘The emergence of adaptive facades offers a new approach for buildings to enhance their resilience against external weather conditions while responding to occupants’demands,thereby improving both indoor environmental quality and energy performance.Appropriate control methods are crucial to achieving these purposes.However,most existing studies for automatic control of blinds have focused on visual comfort,leaving potential for further energy savings by reducing cooling and artificial lighting demands.Additionally,current optimization methods for slat angles are mostly simplified as a discrete process,neglecting the impact of thermal mass in building envelopes.Therefore,this paper aims to explore the energy reduction potential of window blinds by developing an iterative optimization method for devising hourly adaptive control strategies.To this end,a co-simulation platform between EnergyPlus and Python was established for the optimization and a case study in a subtropical city was conducted.The proposed strategies effectively balanced lighting and cooling demands to achieve an overall energy reduction of 7.3%–12.5%compared to reference cases while also ensuring visual comfort by mitigating glare risk and excessive daylight.These advantages were also compared with several simpler control scenarios,with analyses tailored to various glazing types and orientations.Furthermore,the optimal window configurations with blind control strategies for different orientations were determined.The findings also indicated that glass properties markedly impact the performance of control strategies,underscoring the necessity of holistically considering shading components and glazing types in the optimization to achieve optimal performance.
基金supported by the National Key Research and Development Program of China(2023YFF0906502)the Postgraduate Research and Innovation Project of Hunan Province under Grant(CX20240473).
文摘Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.
基金the Russian Foundation for Basic Research(No.15-01-01923A).
文摘A general(abstract)scheme of iterative improvement and optimization on the base of extension,localization principles which would help to generate new concrete methods and algorithms for new problems is proposed.Application to optimal control problems for continuous systems is considered.Visual example is given.
基金supported by the National Science&Technology Pillar Program(2013BAF07B03)Zhejiang Provincial Natural Science Foundation of China(LY13F010009)
文摘An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.
基金supported by the Key Project (2010ZX03003-001-01)the Hi-Tech Research and Development Program of China (2009AA011802)Program for New Century Excellent Talents in University (NCET)
文摘In cognitive radio(CR)systems,efficient spectrum sensing ensures the secondary user(SU)to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of transmission strategy.However,in practice,due to non-zero probabilities of miss detection and false alarm,the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user(PU).In this paper,using energy detection,we maximize the total throughput of SUs by jointly optimizing the detection threshold and transmission strategy in multiband CR systems.A set of iteration based algorithms are proposed to solve this mix-integer programming problem,which show better performance compared with uniform detection threshold selection algorithm suggested by IEEE 802.22 standard.
基金supported by the National Natural Science Foundation of China(Grant Nos.62205259,62075175,62105254,and 62375212)the National Key Laboratory of Infrared Detection Technologies(Grant No.IRDT-23-06)+1 种基金the Fundamental Research Funds for the Central Universities(Grant Nos.XJSJ24028,XJS222202,ZYTS24097,and ZYTS24095)the Open Research Fund of Beijing Key Laboratory of Advanced Optical Remote Sensing Technology.
文摘High-resolution seeing through complex scattering media such as turbid water,biological tissues,and mist is a significant challenge because the strong scattering scrambles the light paths and forms the scattering wall.We propose an active polarized iterative optimization approach for high-resolution imaging through complex scattering media.By acquiring a series of sub-polarized images,we can capture the diverse pattern-illuminated images with various high-frequency component information caused by the Brownian motion of complex scattering materials,which are processed using the common-mode rejection of polarization characteristics to extract target information from scattering medium information.Following that,our computational reconstruction technique employs an iterative optimization algorithm that commences with patternilluminated Fourier ptychography for reconstructing the high-resolution scene.It is extremely important that our approach for high-resolution imaging through complex scattering media is not limited by priori information and optical memory effect.The proposed approach is suitable for not only dynamic but also static scattering media,which may find applications in the biomedicine field,such as skin abnormalities,non-invasive blood flow,and superficial tumors.
基金supported by the National Natural Science Foundation of China(Grant No.61961024)the Top Double 1000 Talent Programme of Jiangxi Province(Grant No.JXSQ2019201055)+1 种基金the Natural Science Foundation of Jiangxi Province(Grant No.20181BAB202001)the Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security(Grant No.AGK201602)。
文摘To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.The eavesdropping on the UR is interfered by a source-based jamming strategy.Under the constraints of unit modulus and total power,the RIS phase shift,the power allocation between the confidential signal and the jamming signal,and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate.The complex multivariable coupling problem is decomposed into three sub-problems,and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation.Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme,the random phase shift scheme,and the no-RIS scheme.
基金Foundation of the National Post-Doctoral Committee
文摘In the present paper, based on the theory of dynamic boundary integral equation, an optimization method for crack identification is set up in the Laplace frequency space, where the direct problem is solved by the author's new type boundary integral equations and a method for choosing the high sensitive frequency region is proposed. The results show that the method proposed is successful in using the information of boundary elastic wave and overcoming the ill-posed difficulties on solution, and helpful to improve the identification precision.
基金supported by the the Fundamental Research Funds for the Central Universities(Grant No.JUSRP202501133)。
文摘In the stability framework of model predictive control(MPC),the size of the stabilizable set(also known as the region of attraction)is dependent on the terminal constraint region.This article aims to investigate the optimization of the terminal region for predictive control of a class of systems with multiplicative uncertainty,aiming to expand the attraction region in MPC.By utilizing a coordinate transformation,we initially develop a structured design for terminal ingredients while considering uncertainties in parameters.Subsequently,we propose novel methods to convert the original nonlinear problem into a linear matrix inequality(LMI)problem with minimal conservatism in the formulation.We propose an iterative learning optimization approach to compute the polytopic terminal region,and its incremental volume is theoretically proven.The efectiveness of the proposed approaches is demonstrated using a benchmark academic example and vehicle lateral dynamics.Through real-time simulation experiments,we demonstrate that the proposed approach can enlarge the domain of attraction as well as reduce the computational complexity of robust MPC systems under parameter uncertainty.
基金Project supported by the National Natural Science Foundation of China(Grant No.60504033)
文摘In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is powerful for the problems characterized by small samples, nonlinearity, high dimension and local minima, support vector regression models are developed for the optimal control of batch processes where end-point properties are required. The model parameters are selected within the Bayesian evidence framework. Based on the model, an iterative method is used to exploit the repetitive nature of batch processes to determine the optimal operating policy. Numerical simulation shows that the iterative optimal control can improve the process performance through iterations.
基金Project supported by the National Natural Science Foundation of China(No.11671106)the Fundamental Research Funds for the Central Universities(No.2016MS33)
文摘This study develops an optimized finite difference iterative （OFDI） scheme for the two-dimensional （2D） viscoelastic wave equation. The OFDI scheme is obtained using a proper orthogonal decomposition （POD） method. It has sufficiently high accuracy with very few unknowns for the 2D viscoelastic wave equation. Existence, stability, and convergence of the OFDI solutions are analyzed. Numerical simulations verify efficiency and feasibility of the proposed scheme.
文摘RSs(Radar Systems)identify and trace targets and are commonly employed in applications like air traffic control and remote sensing.They are necessary for monitoring precise target trajectories.Estimations of RSs are non-linear as the parameters TDEs(time delay Estimations)and Doppler shifts are computed on receipt of echoes where EKFs(Extended Kalman Filters)and UKFs(Unscented Kalman Filters)have not been examined for computations.RSs,certain times result in poor accuracies and SNRs(low signal to noise ratios)especially,while encountering complicated environments.This work proposes IUKFs(Iterated UKFs)to track onlinefilter performances while using optimization techniques to enhance outcomes.The use of cost functions can assist state corrections while lowering costs.A new parameter is optimized using MCEHOs(Mutation Chaotic Elephant Herding Optimizations)by linearly approximating system non-linearity where OIUKFs(Optimized Iterative UKFs)predict a target's unknown parameters.To obtain optimal solutions theoretically,OIUKFs take less iteration,resulting in shorter execution times.The proposed OIUKFs provide numerical approximations which are derivative-free implementations.Simulation evaluation results with estimators show better performances in terms of reduced NMSEs(Normalized Mean Square Errors),RMSEs(Root Mean Squared Errors),SNRs,variances,and better accuracies than current approaches.
文摘This paper describes a new design of the neutral beam manifold based on a more optimized support system.A proposed alternative scheme has presented to replace the former complex manifold supports and internal pipe supports in the final design phase.Both the structural reliability and feasibility were confirmed with detailed analyses.Comparative analyses between two typical types of manifold support scheme were performed.All relevant results of mechanical analyses for typical operation scenarios and fault conditions are presented.Future optimization activities are described,which will give useful information for a refined setting of components in the next phase.
基金supported by National Natural Science Foundation of China(No.61771005)
文摘This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.
基金the State Science and Technology Project of China (No.2001BA204B01).
文摘An iterative optimization strategy is proposed and applied to the steady state optimizing control of the bio-dissimilation process of glycerol to 1,3-propanediol in the presence of model-plant mismatch and input constraints. The scheme is based on the Augmented Integrated System Optimization and Parameter Estimation （AI- SOPE） technique, but a linearization of some performance function in the modified model-based optimization problem of AISOPE is introduced to overcome the difficulty of determining an appropriate penalty parameter. When carrying out the iterative optimization, the penalty coefficient is set to a larger value at the current iteration than at the previous iteration, which can promote the evolution rate of the iterative optimization. Simulation studies illustrate the potential ofthe approach presented for the optimizing control of the bioTdissimilation process of glycerol to 1,3-propanediol. The effects of measurement noise, measured and unmeasured disturbances on the proposed algorithm are also investigated.
基金supported in part by National Key Research and Development Program of China(2016YFB0901900)the Science and Technology Foundation of GEIDCO(SGGEIG00JYJS1900016)
文摘Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades.The key challenges for achieving this goal are carbon emission trading and electricity sector regulation,which are also the major components of the carbon and electricity markets,respectively.In this paper,a joint electricity and carbon market model is proposed to investigate the relationships between electricity price,carbon price,and electricity generation capacity,thereby identifying pathways toward a renewable energy transition under the transactional energy interconnection framework.The proposed model is a dynamically iterative optimization model consisting of upper-level and lower-level models.The upper-level model optimizes power generation and obtains the electricity price,which drives the lower-level model to update the carbon price and electricity generation capacity.The proposed model is verified using the Northeast Asia power grid.The results show that increasing carbon price will result in increased electricity price,along with further increases in renewable energy generation capacity in the following period.This increase in renewable energy generation will reduce reliance on carbon-emitting energy sources,and hence the carbon price will decline.Moreover,the interconnection among zones in the Northeast Asia power grid will enable reasonable allocation of zonal power generation.Carbon capture and storage (CCS) will be an effective technology to reduce the carbon emissions and further realize the emission reduction targets in 2030-2050.It eases the stress of realizing the energy transition because of the less urgency to install additional renewable energy capacity.
基金supported by the National Key Research and Development Program of China(No.2021YFF0502900)the National Natural Science Foundation of China(Nos.62175163,62225505,61935012,61835009,62127819,and 62205220)+2 种基金the Shenzhen Key Projects(No.JCYJ20200109105404067)the Shenzhen Talent Innovation Project(No.RCJC20210706091949022)the Shenzhen Science and Technology Planning Project(No.ZDSYS20210623092006020)。
文摘Fluorescence lifetime imaging can reveal the high-resolution structure of various biophysical and chemical parameters in a microenvironment quantitatively.However,the depth of imaging is generally limited to hundreds of micrometers due to aberration and light scattering in biological tissues.This paper introduces an iterative multi-photon adaptive compensation technique(IMPACT)into a two-photon fluorescence lifetime microscopy system to successfully overcome aberrations and multiple scattering problems in deep tissues.It shows that 400 correction modes can be achieved within 5 min,which was mainly limited by the frame rate of a spatial light modulator.This system was used for high-resolution imaging of mice brain tissue and live zebrafish,further verifying its superior performance in imaging quality and photon accumulation speed.
文摘Background Aiming at free-view exploration of complicated scenes,this paper presents a method for interpolating views among multi RGB cameras.Methods In this study,we combine the idea of cost volume,which represent 3 D information,and 2 D semantic segmentation of the scene,to accomplish view synthesis of complicated scenes.We use the idea of cost volume to estimate the depth and confidence map of the scene,and use a multi-layer representation and resolution of the data to optimize the view synthesis of the main object.Results/Conclusions By applying different treatment methods on different layers of the volume,we can handle complicated scenes containing multiple persons and plentiful occlusions.We also propose the view-interpolation→multi-view reconstruction→view interpolation pipeline to iteratively optimize the result.We test our method on varying data of multi-view scenes and generate decent results.
基金Project(60674063) supported by the National Natural Science Foundation of China
文摘The quality prediction of tube hollow model based on the variance staged multiway partial least square (MPLS) method was proposed.The key aspects of staged decomposition of the productive data,calculation of the variance value,modeling,and on-lined prediction in the variance-staged MPLS method were introduced.Based on the model,iterative optimal control method was used for quality control of tube hollow.The experimental results show that the obvious benefits of this method are low maintenance cost,good real time function,high reliability precision,and practical application to on-line prediction and optimization on the quality of tube hollow.
基金Supported by the National Natural Science Foundation of China(50978083)the Fundamental Research Funds for the Central Universities(2010B02814)
文摘This paper proposes a sensitivity analysis method for engineering parameters using interval analyses.This method substantially extends the application of interval analysis method.In this scheme,parameter intervals and decision-making target intervals are determined using the interval analysis method.As an example,an inverse analysis method for uncertainty is presented.The intervals of unknown parameters can be obtained by sampling measured data.Even for limited measured data,robust results can also be obtained with the inverse analysis method,which can be intuitively evaluated by the uncertainty expressed in terms of an interval.For complex nonlinear problems,an iteratively optimized inverse analysis model is proposed.In a given set of loose parameter intervals,all the unknown parameter intervals that satisfy the measured information can be obtained by an iteratively optimized inverse analysis model.The influences of measured precisions and the number of parameters on the results of the inverse analysis are evaluated.Finally,the uniqueness of the interval inverse analysis method is discussed.
