The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate...Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.展开更多
This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with ...This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with 84 students from a middle school selected as the research subjects(44 in the experimental group and 40 in the control group).The experimental group used the reflective feedback model,while the control group used the factual feedback model.The results show that,compared with factual feedback,the reflective feedback model based on the pedagogical agent significantly improves students’problem-solving ability,especially at the action and thinking levels.In addition,this model effectively reduces students’cognitive load,especially in terms of internal and external load.展开更多
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses ...The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.展开更多
Written feedback in English writing classes serves as the primary mode of feedback.By comparing direct corrective feedback and indirect corrective feedback in addressing content and form,this paper argues that indirec...Written feedback in English writing classes serves as the primary mode of feedback.By comparing direct corrective feedback and indirect corrective feedback in addressing content and form,this paper argues that indirect corrective feedback better aligns with the needs of English majors.Multiple factors influence the choice of written feedback methods,and teachers should carefully select the most appropriate approach based on student characteristics to maximize the effectiveness of feedback.展开更多
Although substantial research shows the effectiveness of written corrective feedback(WCF)in treating simple grammar structures,more research is still needed to refute Truscott’s claim that WCF may not work on complex...Although substantial research shows the effectiveness of written corrective feedback(WCF)in treating simple grammar structures,more research is still needed to refute Truscott’s claim that WCF may not work on complex grammar structures.Similarly,a previous body of research has shown that the degree of explicitness of feedback moderates the efficacy of WCF.However,most WCF studies have systematically manipulated only direct corrective feedback.The current study was therefore conducted to fill these gaps in the literature.To this end,five intact classes of Functional English were recruited and later randomly assigned to four treatment groups:DCF,DCF+ME,ICF,and ICF+ME,and one control group that received no feedback.All the groups took part in three WCF treatment sessions,during which they wrote two different pieces:a news report and a picture description.Later,only the treatment groups received the WCF.The WCF’s effectiveness was measured by writing tests and grammaticality judgment tasks(GJT).The results demonstrated that WCF helped L2 learners improve their grammatical accuracy of passive voice tenses.The study further showed that the group that received the most explicit type of WCF fared better than the ones that received the least explicit type of WCF.Important pedagogical implications for ESL/EFL teachers are discussed.展开更多
In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the d...In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.展开更多
Direct comparison of the difference in biomass between live and sterilized soils may result in deviations in biological plant-soil feedback(B-PSF)due to changes induced by sterilization in bulk soil microorganisms,soi...Direct comparison of the difference in biomass between live and sterilized soils may result in deviations in biological plant-soil feedback(B-PSF)due to changes induced by sterilization in bulk soil microorganisms,soil structure,and nutrient availability.The sterilization-induced deviation(sterilization-effect,SS_(c))to often-used method B-PSF_(ou) was corrected by adding a parallel experiment without conditioning by any plants(B-PSF_(c)).Plant-soil feedback experiments were conducted for two plants with contrasting in root traits and rhizosphere microbial community to test the reliability of the method(Kalidium foliatum and Reaumuria songaric).The specific root length(SRL),root tissue density(RTD)and of R.songarica was higher compared to that of K.foliatum,but the root diameter(RAD)of it was significantly lower than that of K.foliatum.The plasticity of root traits of K.foliatum was stronger than that of R.songarica.The B-PSF_(ou) of K.foliatum was four times negative than B-PSF_(c),whereas there was no statistically significant difference of B-PSF_(ou) and B-PSF_(c) for R.songarica.The correlation between B-PSF_(c) and the relative abundance of pathogens and EcMF was found to be stronger compared to B-PSF_(ou).We proposed method corrects the deviation in B-PSF.The variation of deviation between species may be related to root traits.展开更多
We theoretically investigate a cooling scheme assisted by a quantum well(QW)and coherent feedback within a hybrid optomechanical system.Although the exciton mode in the QW and the mechanical resonator(MR)are initially...We theoretically investigate a cooling scheme assisted by a quantum well(QW)and coherent feedback within a hybrid optomechanical system.Although the exciton mode in the QW and the mechanical resonator(MR)are initially uncoupled,their interaction via the microcavity field leads to an indirect exciton-mode–mechanical-mode coupling.The coherent feedback loop is applied by feeding back a fraction of the output field of the cavity through a controllable beam splitter to the cavity’s input mirror.It is shown that the cooling capability is enhanced by effectively suppressing the Stokes process through coupling with the QW.Furthermore,the effect of the anti-Stokes process is enhanced through the application of the coherent feedback loop.This particular system configuration enables cooling of the mechanical resonator even in the unresolved sideband regime(USR).This study has some important guiding significance in the field of quantum information processing.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Background Haptic feedback plays a crucial role in virtual reality(VR)interaction,helping to improve the precision of user operation and enhancing the immersion of the user experience.Instrumental haptic feedback in v...Background Haptic feedback plays a crucial role in virtual reality(VR)interaction,helping to improve the precision of user operation and enhancing the immersion of the user experience.Instrumental haptic feedback in virtual environments is primarily realized using grounded force or vibration feedback devices.However,improvements are required in terms of the active space and feedback realism.Methods We propose a lightweight and flexible haptic feedback glove that can haptically render objects in VR environments via kinesthetic and vibration feedback,thereby enabling users to enjoy a rich virtual piano-playing experience.The kinesthetic feedback of the glove relies on a cable-pulling mechanism that rotates the mechanism and pulls the two cables connected to it,thereby changing the amount of force generated to simulate the hardness or softness of the object.Vibration feedback is provided by small vibration motors embedded in the bottom of the fingertips of the glove.We designed a piano-playing scenario in the virtual environment and conducted user tests.The evaluation metrics were clarity,realism,enjoyment,and satisfaction.Results A total of 14 subjects participated in the test,and the results showed that our proposed glove scored significantly higher on the four evaluation metrics than the nofeedback and vibration feedback methods.Conclusions Our proposed glove significantly enhances the user experience when interacting with virtual objects.展开更多
Force feedback bilateral teleoperation represents a pivotal advancement in control technology,finding widespread application in hazardous material transportation,perilous environments,space and deep-sea exploration,an...Force feedback bilateral teleoperation represents a pivotal advancement in control technology,finding widespread application in hazardous material transportation,perilous environments,space and deep-sea exploration,and healthcare domains.This paper traces the evolutionary trajectory of force feedback bilateral teleoperation from its conceptual inception to its current complexity.It elucidates the fundamental principles underpinning interaction forces and tactile exchanges,with a specific emphasis on the crucial role of tactile devices.In this review,a quantitative analysis of force feedback bilateral teleoperation development trends from 2011 to 2024 has been conducted,utilizing published journal article data as the primary source of information.The review accentuates classical control frameworks and algorithms,while also delving into existing research advancements and prospec-tive breakthrough directions.Moreover,it explores specific practical scenarios ranging from intricate surgeries to hazardous environment exploration,underscoring the technology’s potential to revolutionize industries by augmenting human manipulation of remote systems.This underscores the pivotal role of force feedback bilateral teleoperation as a transformative human-machine interface,capable of shaping flexible control strategies and addressing technological bottlenecks.Future research endeavors in force feedback bilateral teleoperation are expected to prioritize the creation of more immersive experiences,overcoming technical hurdles,fortifying human-machine collaboration,and broadening application domains,particularly within the realms of medical intervention and hazardous environments.With the continuous progression of technology,the integration of human intelligence and robotic capabilities is expected to produce more innovations and breakthroughs in the field of automatic control.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective metho...Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.展开更多
Channel state information(CSI)is essen-tial to unlock the potential of reconfigurable intelli-gent surfaces(RISs)in wireless communication sys-tems.Since massive RIS elements are typically imple-mented without baseban...Channel state information(CSI)is essen-tial to unlock the potential of reconfigurable intelli-gent surfaces(RISs)in wireless communication sys-tems.Since massive RIS elements are typically imple-mented without baseband signal processing capabili-ties,limited CSI feedback is necessary when design-ing the reflection/refraction coefficients of the RIS.In this article,the unique RIS-assisted channel features,such as the RIS position-dependent channel fluctua-tion,the ultra-high dimensional sub-channel matrix,and the structured sparsity,are distilled from recent advances in limited feedback and used as guidelines for designing feedback schemes.We begin by il-lustrating the use cases and the corresponding chal-lenges associated with RIS feedback.We then discuss how to leverage techniques such as channel customiza-tion,structured-sparsity,autoencoders,and others to reduce feedback overhead and complexity when de-vising feedback schemes.Finally,we identify poten-tial research directions by considering the unresolved challenges,the new RIS architecture,and the integra-tion with multi-modal information and artificial intel-ligence.展开更多
This study investigates the nonlinear resonance responses of suspended cables subjected to multi-frequency excitations and time-delayed feedback.Two specific combinations and simultaneous resonances are selected for d...This study investigates the nonlinear resonance responses of suspended cables subjected to multi-frequency excitations and time-delayed feedback.Two specific combinations and simultaneous resonances are selected for detailed examination.Initially,utilizing Hamilton’s variational principle,a nonlinear vibration control model of suspended cables under multi-frequency excitations and longitudinal time-delayed velocity feedback is developed,and the Galerkin method is employed to obtain the discrete model.Subsequently,focusing solely on single-mode discretization,analytical solutions for the two simultaneous resonances are derived using the method of multiple scales.The frequency response equations are derived,and the stability analysis is presented for two simultaneous resonance cases.The results demonstrate that suspended cables exhibit complex nonlinearity under multi-frequency excitations.Multiple solutions under multi-frequency excitation can be distinguished through the frequency–response and the detuning-phase curves.By adjusting the control gain and time delay,the resonance range,response amplitude,and phase of suspended cables can be modified.展开更多
This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model E...This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model EC-Earth3.Our findings indicate that vegetation changes significantly influence the global monsoon area and precipitation patterns,especially in the North African and Indian monsoon regions.The North African monsoon region experienced the most substantial increase in vegetation during both the LIG and MH,resulting in significant increases in monsoonal precipitation by 9.8%and 6.0%,respectively.The vegetation feedback also intensified the Saharan Heat Low,strengthened monsoonal flows,and enhanced precipitation over the North African monsoon region.In contrast,the Indian monsoon region exhibited divergent responses to vegetation changes.During the LIG,precipitation in the Indian monsoon region decreased by 2.2%,while it increased by 1.6%during the MH.These differences highlight the complex and region-specific impacts of vegetation feedback on monsoon systems.Overall,this study demonstrates that vegetation feedback exerts distinct influences on the global monsoon during the MH and LIG.These findings highlight the importance of considering vegetation-climate feedback in understanding past monsoon variability and in predicting future climate change impacts on monsoon systems.展开更多
Purpose–This study aims to propose a novel identification method to accurately estimate linear and nonlinear dynamics in permanent magnet synchronous linear motor(PMSLM)based on the time-domain analysis of relay feed...Purpose–This study aims to propose a novel identification method to accurately estimate linear and nonlinear dynamics in permanent magnet synchronous linear motor(PMSLM)based on the time-domain analysis of relay feedback.Design/methodology/approach–A mathematical model of the PMSLM-based servo-mechanical system was first established,incorporating the aforementioned nonlinearities.The model’s velocity response was derived by analyzing its behavior as a first-order system under arbitrary input.To induce oscillatory dynamics,an ideal relay with artificially introduced dead-time components was then integrated into the servo-mechanism.Depending on the oscillations and the time-domain analysis,nonlinear formulas were deduced according to the velocity response of the servo-mechanism.Afterwards,the unknown model parameters can be solved on account of the cost function which utilizes the discrepancy between nominal position characteristics and temporary position characteristics,both of which are extracted from the oscillations.The proposed recognition method was validated through a twostage process:(1)numerical simulation and calculation,followed by(2)real-time experimental verification on a direct-drive servo platform.Subsequently,leveraging the identification results,a novel control strategy was developed and its tracking performance was benchmarked against conventional control schemes.Findings–Simulation results demonstrate that the proposed method achieves estimation accuracy within 8%.Building on this,a novel control strategy is developed by incorporating both friction pulsation and force pulsation identification results into the feedforward compensator.Comparative experiments reveal that this strategy significantly enhances tracking and positioning performance over traditional control schemes.In a word,this new identification method can be used in different process control and servo control systems.Moreover,parameter auto-tuning,feed forward compensation or disturbance observer can be investigated based on the obtained information to improve the system stability and control accuracy.Originality/value–It is of great significance for the performance improvement of rail transit motor control equipment,such as electro-mechanical braking systems.By enhancing the efficiency of motor control,the performance of the product will be more outstanding.展开更多
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金supported in part by the National Natural Science Foundation of China(62173051)the Fundamental Research Funds for the Central Universities(2024CDJCGJ012,2023CDJXY-010)+1 种基金the Chongqing Technology Innovation and Application Development Special Key Project(CSTB2022TIADCUX0015,CSTB2022TIAD-KPX0162)the China Postdoctoral Science Foundation(2024M763865)
文摘Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.
基金023 Zhejiang Provincial Department of Education General Project:Research on an interdisciplinary teaching model to promote the development of computational thinking in the context of the new curriculum standards[Grant NO:Y202351596]Key Project of Zhejiang Provincial Education Science Planning:Research on an interdisciplinary teaching model to promote students’computational thinking from multiple analytical perspectives[Grant NO:2025SB103].
文摘This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with 84 students from a middle school selected as the research subjects(44 in the experimental group and 40 in the control group).The experimental group used the reflective feedback model,while the control group used the factual feedback model.The results show that,compared with factual feedback,the reflective feedback model based on the pedagogical agent significantly improves students’problem-solving ability,especially at the action and thinking levels.In addition,this model effectively reduces students’cognitive load,especially in terms of internal and external load.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the Special Funds Project for the Transformation of Scientific and Technological Achievements of Jiangsu Province,China(No.BA2023039)+1 种基金the National Natural Science Foundation of China(No.52075262)the Fundamental Research Funds for the Central Universities,China(No.30922010706).
文摘The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.
文摘Written feedback in English writing classes serves as the primary mode of feedback.By comparing direct corrective feedback and indirect corrective feedback in addressing content and form,this paper argues that indirect corrective feedback better aligns with the needs of English majors.Multiple factors influence the choice of written feedback methods,and teachers should carefully select the most appropriate approach based on student characteristics to maximize the effectiveness of feedback.
文摘Although substantial research shows the effectiveness of written corrective feedback(WCF)in treating simple grammar structures,more research is still needed to refute Truscott’s claim that WCF may not work on complex grammar structures.Similarly,a previous body of research has shown that the degree of explicitness of feedback moderates the efficacy of WCF.However,most WCF studies have systematically manipulated only direct corrective feedback.The current study was therefore conducted to fill these gaps in the literature.To this end,five intact classes of Functional English were recruited and later randomly assigned to four treatment groups:DCF,DCF+ME,ICF,and ICF+ME,and one control group that received no feedback.All the groups took part in three WCF treatment sessions,during which they wrote two different pieces:a news report and a picture description.Later,only the treatment groups received the WCF.The WCF’s effectiveness was measured by writing tests and grammaticality judgment tasks(GJT).The results demonstrated that WCF helped L2 learners improve their grammatical accuracy of passive voice tenses.The study further showed that the group that received the most explicit type of WCF fared better than the ones that received the least explicit type of WCF.Important pedagogical implications for ESL/EFL teachers are discussed.
文摘In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.
基金supported by Gansu Province Science and Technology Project(Grant No.21JR7RA070)the Natural Science Foundation of Gansu Province,China(Grant No.22JR5RA051)the Central Government Guides Local Funds Project for Science and Technology Development(Grant No.23ZYQHO_(2)98).
文摘Direct comparison of the difference in biomass between live and sterilized soils may result in deviations in biological plant-soil feedback(B-PSF)due to changes induced by sterilization in bulk soil microorganisms,soil structure,and nutrient availability.The sterilization-induced deviation(sterilization-effect,SS_(c))to often-used method B-PSF_(ou) was corrected by adding a parallel experiment without conditioning by any plants(B-PSF_(c)).Plant-soil feedback experiments were conducted for two plants with contrasting in root traits and rhizosphere microbial community to test the reliability of the method(Kalidium foliatum and Reaumuria songaric).The specific root length(SRL),root tissue density(RTD)and of R.songarica was higher compared to that of K.foliatum,but the root diameter(RAD)of it was significantly lower than that of K.foliatum.The plasticity of root traits of K.foliatum was stronger than that of R.songarica.The B-PSF_(ou) of K.foliatum was four times negative than B-PSF_(c),whereas there was no statistically significant difference of B-PSF_(ou) and B-PSF_(c) for R.songarica.The correlation between B-PSF_(c) and the relative abundance of pathogens and EcMF was found to be stronger compared to B-PSF_(ou).We proposed method corrects the deviation in B-PSF.The variation of deviation between species may be related to root traits.
基金supported by the National Natural Science Foundation of China(Grant Nos.62061028 and 62461035)the Key Project of Natural Science Foundation of Jiangxi Province(Grant No.20232ACB202003)+2 种基金the Finance Science and Technology Special“contract system”Project of Nanchang University Jiangxi Province(Grant No.ZBG20230418015)the Natural Science Foundation of Chongqing(Grant No.CSTB2024NSCQ-MSX0412)the Opening Project of Shanghai Key Laboratory of Special Artificial Microstructure Materials and Technology(Grant No.ammt2021A-4).
文摘We theoretically investigate a cooling scheme assisted by a quantum well(QW)and coherent feedback within a hybrid optomechanical system.Although the exciton mode in the QW and the mechanical resonator(MR)are initially uncoupled,their interaction via the microcavity field leads to an indirect exciton-mode–mechanical-mode coupling.The coherent feedback loop is applied by feeding back a fraction of the output field of the cavity through a controllable beam splitter to the cavity’s input mirror.It is shown that the cooling capability is enhanced by effectively suppressing the Stokes process through coupling with the QW.Furthermore,the effect of the anti-Stokes process is enhanced through the application of the coherent feedback loop.This particular system configuration enables cooling of the mechanical resonator even in the unresolved sideband regime(USR).This study has some important guiding significance in the field of quantum information processing.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
基金Supported by the Natienal Natural Science Foundation of China(U23A20287).
文摘Background Haptic feedback plays a crucial role in virtual reality(VR)interaction,helping to improve the precision of user operation and enhancing the immersion of the user experience.Instrumental haptic feedback in virtual environments is primarily realized using grounded force or vibration feedback devices.However,improvements are required in terms of the active space and feedback realism.Methods We propose a lightweight and flexible haptic feedback glove that can haptically render objects in VR environments via kinesthetic and vibration feedback,thereby enabling users to enjoy a rich virtual piano-playing experience.The kinesthetic feedback of the glove relies on a cable-pulling mechanism that rotates the mechanism and pulls the two cables connected to it,thereby changing the amount of force generated to simulate the hardness or softness of the object.Vibration feedback is provided by small vibration motors embedded in the bottom of the fingertips of the glove.We designed a piano-playing scenario in the virtual environment and conducted user tests.The evaluation metrics were clarity,realism,enjoyment,and satisfaction.Results A total of 14 subjects participated in the test,and the results showed that our proposed glove scored significantly higher on the four evaluation metrics than the nofeedback and vibration feedback methods.Conclusions Our proposed glove significantly enhances the user experience when interacting with virtual objects.
基金supported by the MSIT(Ministry of Science and ICT),Republic of Korea,under the Convergence Security Core Talent Training Business Support Program(IITP-2024-RS-2024-00423071)supervised by the IITP(Institute of Information&Communications Technology Planning&Evaluation)supported by Sichuan Science and Technology Program(2023YFSY0026,2023YFH0004).
文摘Force feedback bilateral teleoperation represents a pivotal advancement in control technology,finding widespread application in hazardous material transportation,perilous environments,space and deep-sea exploration,and healthcare domains.This paper traces the evolutionary trajectory of force feedback bilateral teleoperation from its conceptual inception to its current complexity.It elucidates the fundamental principles underpinning interaction forces and tactile exchanges,with a specific emphasis on the crucial role of tactile devices.In this review,a quantitative analysis of force feedback bilateral teleoperation development trends from 2011 to 2024 has been conducted,utilizing published journal article data as the primary source of information.The review accentuates classical control frameworks and algorithms,while also delving into existing research advancements and prospec-tive breakthrough directions.Moreover,it explores specific practical scenarios ranging from intricate surgeries to hazardous environment exploration,underscoring the technology’s potential to revolutionize industries by augmenting human manipulation of remote systems.This underscores the pivotal role of force feedback bilateral teleoperation as a transformative human-machine interface,capable of shaping flexible control strategies and addressing technological bottlenecks.Future research endeavors in force feedback bilateral teleoperation are expected to prioritize the creation of more immersive experiences,overcoming technical hurdles,fortifying human-machine collaboration,and broadening application domains,particularly within the realms of medical intervention and hazardous environments.With the continuous progression of technology,the integration of human intelligence and robotic capabilities is expected to produce more innovations and breakthroughs in the field of automatic control.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金supported by the Fund of Key Laboratory of Biomedical Engineering of Hainan Province(No.BME20240001)the STI2030-Major Projects(No.2021ZD0200104)the National Natural Science Foundations of China under Grant 61771437.
文摘Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.
基金supported in part by the Key Technologies Research and Development Program of Jiangsu(Prospective and Key Technologies for Industry)under Grant BE2023022 and BE2023022-1in part by National Natural Science Foundation of China(NSFC)under Grant 62401137,62401640,and 62231009+3 种基金in part by the Natural Science Foundation of Jiangsu Province under Grant BK20241281in part by the China National Postdoctoral Program for Innovative Talents under Grant BX20230065 and 2024M750421in part by the Jiangsu Excellent Postdoctoral Program under Grant 2023ZB476in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515110732.
文摘Channel state information(CSI)is essen-tial to unlock the potential of reconfigurable intelli-gent surfaces(RISs)in wireless communication sys-tems.Since massive RIS elements are typically imple-mented without baseband signal processing capabili-ties,limited CSI feedback is necessary when design-ing the reflection/refraction coefficients of the RIS.In this article,the unique RIS-assisted channel features,such as the RIS position-dependent channel fluctua-tion,the ultra-high dimensional sub-channel matrix,and the structured sparsity,are distilled from recent advances in limited feedback and used as guidelines for designing feedback schemes.We begin by il-lustrating the use cases and the corresponding chal-lenges associated with RIS feedback.We then discuss how to leverage techniques such as channel customiza-tion,structured-sparsity,autoencoders,and others to reduce feedback overhead and complexity when de-vising feedback schemes.Finally,we identify poten-tial research directions by considering the unresolved challenges,the new RIS architecture,and the integra-tion with multi-modal information and artificial intel-ligence.
基金supported in part by the National Natural Science Foundation of China(Grant No.12432001)Natural Science Foundation of Hunan Province(Grant Nos.2023JJ60527,2023JJ30152,and 2023JJ30259)the Natural Science Foundation of Changsha(KQ2202133).
文摘This study investigates the nonlinear resonance responses of suspended cables subjected to multi-frequency excitations and time-delayed feedback.Two specific combinations and simultaneous resonances are selected for detailed examination.Initially,utilizing Hamilton’s variational principle,a nonlinear vibration control model of suspended cables under multi-frequency excitations and longitudinal time-delayed velocity feedback is developed,and the Galerkin method is employed to obtain the discrete model.Subsequently,focusing solely on single-mode discretization,analytical solutions for the two simultaneous resonances are derived using the method of multiple scales.The frequency response equations are derived,and the stability analysis is presented for two simultaneous resonance cases.The results demonstrate that suspended cables exhibit complex nonlinearity under multi-frequency excitations.Multiple solutions under multi-frequency excitation can be distinguished through the frequency–response and the detuning-phase curves.By adjusting the control gain and time delay,the resonance range,response amplitude,and phase of suspended cables can be modified.
基金supported by the Swedish Research Council(Vetenskapsradet,Grant No.202203129)the Project of Youth Science and Technology Fund of Gansu Province(Grant No.24JRRA439)partially funded by the Swedish Research Council(Vetenskapsradet,Grant No.2022-06725)。
文摘This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model EC-Earth3.Our findings indicate that vegetation changes significantly influence the global monsoon area and precipitation patterns,especially in the North African and Indian monsoon regions.The North African monsoon region experienced the most substantial increase in vegetation during both the LIG and MH,resulting in significant increases in monsoonal precipitation by 9.8%and 6.0%,respectively.The vegetation feedback also intensified the Saharan Heat Low,strengthened monsoonal flows,and enhanced precipitation over the North African monsoon region.In contrast,the Indian monsoon region exhibited divergent responses to vegetation changes.During the LIG,precipitation in the Indian monsoon region decreased by 2.2%,while it increased by 1.6%during the MH.These differences highlight the complex and region-specific impacts of vegetation feedback on monsoon systems.Overall,this study demonstrates that vegetation feedback exerts distinct influences on the global monsoon during the MH and LIG.These findings highlight the importance of considering vegetation-climate feedback in understanding past monsoon variability and in predicting future climate change impacts on monsoon systems.
文摘Purpose–This study aims to propose a novel identification method to accurately estimate linear and nonlinear dynamics in permanent magnet synchronous linear motor(PMSLM)based on the time-domain analysis of relay feedback.Design/methodology/approach–A mathematical model of the PMSLM-based servo-mechanical system was first established,incorporating the aforementioned nonlinearities.The model’s velocity response was derived by analyzing its behavior as a first-order system under arbitrary input.To induce oscillatory dynamics,an ideal relay with artificially introduced dead-time components was then integrated into the servo-mechanism.Depending on the oscillations and the time-domain analysis,nonlinear formulas were deduced according to the velocity response of the servo-mechanism.Afterwards,the unknown model parameters can be solved on account of the cost function which utilizes the discrepancy between nominal position characteristics and temporary position characteristics,both of which are extracted from the oscillations.The proposed recognition method was validated through a twostage process:(1)numerical simulation and calculation,followed by(2)real-time experimental verification on a direct-drive servo platform.Subsequently,leveraging the identification results,a novel control strategy was developed and its tracking performance was benchmarked against conventional control schemes.Findings–Simulation results demonstrate that the proposed method achieves estimation accuracy within 8%.Building on this,a novel control strategy is developed by incorporating both friction pulsation and force pulsation identification results into the feedforward compensator.Comparative experiments reveal that this strategy significantly enhances tracking and positioning performance over traditional control schemes.In a word,this new identification method can be used in different process control and servo control systems.Moreover,parameter auto-tuning,feed forward compensation or disturbance observer can be investigated based on the obtained information to improve the system stability and control accuracy.Originality/value–It is of great significance for the performance improvement of rail transit motor control equipment,such as electro-mechanical braking systems.By enhancing the efficiency of motor control,the performance of the product will be more outstanding.
