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Relative Motion Based Predictive Adaptive Control:A Case Study of AUV 3D Trajectory Tracking 认领 引用
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作者 Daxiong Ji Xinwei Wang Yuanchang Liu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第2期492-494,共3页
Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the... Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the-art predictive adaptive controller(PAC)is proposed with a distinct dual closed-loop structure. 展开更多
关键词 adaptive controller pac autonomous underwater vehicle auv three predictive adaptive control relative motion D trajectory tracking hydrodynamics closed loop structure complex hydrodynamicsa
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AMVT-NMN:Adaptive Multi-Scale Vision Transformer with Neuromorphic Memory Networks for Enhanced Lung Cancer Detection 认领 引用
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作者 Wariyo Godana Arero Yaqin Zhao +6 位作者 Mudasir Ahmad Wani Pir Noman Ahmad Kashish Ara Shakil Sadique Ahmad Sidrak Habtemariam Teredda Merhawit Berhane Teklu Longwen Wu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期1236-1262,共27页
Lung cancer accounts for the highest number of cancer deaths globally,underscoring the urgent need for early and precise detection to enhance patient outcomes.While deep learning has made remarkable strides in analyzi... Lung cancer accounts for the highest number of cancer deaths globally,underscoring the urgent need for early and precise detection to enhance patient outcomes.While deep learning has made remarkable strides in analyzing medical images,current approaches face a fundamental challenge.They cannot adequately capture detailed local patterns and broader contextual relationships within lung Computed tomography(CT)scans.To address this limitation,we introduce AMVT-NMN(adaptive multi-scale vision transformer with neuromorphic memory networks),which combines three complementary mechanisms.The dynamic adaptive kernel networks component intelligently adjusts receptive field sizes based on input characteristics,enabling flexible feature capture across multiple scales.The neuromorphic contextual memory attention module draws inspiration from how human memory systems process information,maintaining a dynamic record of diagnostically relevant patterns to inform current predictions.The hierarchical cross-scale fusion mechanism with learnable weights synthesizes information from different resolution levels through adaptive weighting.Testing on the Iraq-Oncology Teaching Hospital/National Center for Cancer Diseases(IQOTHNCCD)dataset demonstrates strong performance:97.9%accuracy,96.5%sensitivity,98.7%specificity,and 99.2%Area under the Curve-Receiver Operating Characteristic(AUC-ROC).These results surpass existing methods such as CNN-GD,which achieved 97.2%accuracy.Notably,the high specificity translates to fewer false alarms,potentially reducing unnecessary biopsies and follow-up imaging outcomes that matter considerably in clinical practice.Result of AMVT-NMN generalization to the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI),Lung nodule analysis(LUNA16),and Non-Small Cell Lung Cancer(NSCLC)-Radiomics datasets showed AUCs of 96.5%,92.8%,and 97.2%,respectively.Ablation experiments confirm that each architectural element of AMVT-NMN contributes meaningfully to overall performance.Five-fold cross-validation yielded consistent results(97.71±0.57%),indicating reliable performance across different patient subsets.The memory-augmented design shows particular promise for handling diagnostically ambiguous cases.It is focused on pattern recognition and computational intelligence,which is useful for coping with uncertain information in intelligent diagnosis systems,meeting the growing trend for trusted artificial intelligence(AI)in decision-making. 展开更多
关键词 Adaptive multi-scale vision transformer dynamic adaptive kernel networks hierarchical cross-scale fusion lung cancer detection neuromorphic memory networks
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Real-Time Feature Detection for Booster Recovery:An Adaptive Harris Framework Integrating Scharr Vectorized Gradients and Dilation-Based NMS 认领 引用
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作者 Bowei Xu Cungui Yu +1 位作者 Jianlin Zhong Qing He 《Journal of Harbin Institute of Technology(New Series)》 CAS 2026年第3期15-31,共17页
In rocket booster recovery missions,robust visual perception is critical for real-time localization and landing control,but complex environments,including noise,illumination variations,and occlusion,severely degrade t... In rocket booster recovery missions,robust visual perception is critical for real-time localization and landing control,but complex environments,including noise,illumination variations,and occlusion,severely degrade the accuracy,repeatability,and localization precision of traditional corner detectors,often resulting in false detections,missed keypoints,and reduced real-time reliability.To address these challenges,an Adaptive Robust Harris(ARH)corner detection algorithm is proposed in this study.The method integrates four innovations:1)Scharr operator-based gradient computation for enhanced edge response;2)An adaptive thresholding via statistical analysis of Harris responses to improve noise robustness;3)A hybrid approach combining dilation-accelerated Non-Maximum Suppression(NMS)and sub-pixel refinement using OpenCV's goodFeaturesToTrack,reducing redundancy and achieving precise localization(average displacement:0.0458 pixels);4)Vectorized computation replacing explicit loops,optimizing runtime by40%.Experimental validation demonstrates ARH's superior performance:high repeatability(≈0.85)under Gaussian noise,20%feature reduction in motion blur(vs.21%for Harris and 82%for SIFT),and stable keypoints under rotation.Computational complexity analysis reveals that adaptive thresholding is optimized from O(N)to O(1),while NMS efficiency improves by 50%.These advancements position ARH as a high-precision,real-time solution for visioncritical tasks in aerospace applications,such as tracking rocket boosters and providing landing assistance. 展开更多
关键词 Adaptive Robust Harris(ARH) Scharr operator adaptive thresholding Non⁃Maximum Suppression(NMS) complex environments rocket booster recovery
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A Continuous-Time Framework of Model-Free Adaptive Control for Nonlinear Plants 认领 引用
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作者 Hao Yu Wangjiang Li +2 位作者 Linxin Che Dawei Shi Zhongsheng Hou 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第4期966-982,共17页
Continuous-time model-free adaptive control frameworks are proposed in this paper for solving tracking problems of unknown nonlinear plants described by high-order differential equations.To tackle situations where no ... Continuous-time model-free adaptive control frameworks are proposed in this paper for solving tracking problems of unknown nonlinear plants described by high-order differential equations.To tackle situations where no form or structural information of plant models is present,the first step involves introducing continuous-time dynamic linearization techniques to create data models.Based on different ways for generating control inputs,two kinds of dynamic linearization processes for continuous-time nonlinear plants are established for the first time,where the nonlinear plants are parameterized by a time-varying linear data model.In the first dynamic linearization model(DLM),the control input is calculated by designating its derivative while the second one gives directly control inputs.Then,after acquiring different dynamic linearization models,based on traditional backstepping methods,adaptive laws are proposed to learn the timevarying parameters in DLMs and the corresponding model-free adaptive controllers are designed.The conditions on designable parameters for the proposed controllers are provided to ensure semi-global practical stabilization and arbitrarily desirable ultimate tracking accuracy.Moreover,to eliminate the effects of unknown equilibrium points on tracking accuracy,a continuoustime model-free adaptive controller with pure integral terms is proposed under the second dynamic linearization model.Finally,several practical and numerical examples are simulated to illustrate the feasibility and efficiency of the proposed results. 展开更多
关键词 Backstepping methods continuous-time systems dynamic linearization model-free adaptive control (MFAC) nonlinear systems
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LL-Refiner:Learning Adaptive Refinement for Ultra-High-Definition Low-Light Image Enhancement 认领 引用
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作者 Xunpeng Yi Qinglong Yan +4 位作者 Yibing Zhang Zongrong Li Hao Zhang Zhanchuan Cai Jiayi Ma 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1288-1300,共13页
Low-light image enhancement aims to address various degradations in low-light conditions,such as low illumination,noise pollution,color distortion,and missing scene content.With advances in digital imaging technology,... Low-light image enhancement aims to address various degradations in low-light conditions,such as low illumination,noise pollution,color distortion,and missing scene content.With advances in digital imaging technology,the resolution of captured images has seen substantial improvements.This poses new challenges in achieving good enhancement performance for multiscale details in ultra-high-definition images,as well as in managing the overhead for supporting the use of consumer-grade GPUs.In this paper,we proposed learning the adaptive refinement framework for ultra-high-definition image enhancement,termed LL-Refiner.It integrates the advantages of hierarchical adaptive refinement guided by coarse enhancement results to enhance the ultra-high-definition images.In detail,firstly,we conduct the coarse enhancement on the low resolution image by employing a Transformer-based coarse enhancement network.Secondly,the coarse enhancement output is fed into the adapted refinement injection.It assigns resolution-aware inputs as guidance to the corresponding adaptive aggregation module,which interacts with the backbone features of the adaptive refinement network.Ultimately,the adaptive refinement network incorporates a combination of hierarchical dense residual connection modules and lightweight convolutional modules at different resolution stages.Also,it integrates a multi-scale enhanced perceptual loss to progressively achieve ultra-high-definition image enhancement.Extensive experiments on ultra-high-definition image enhancement validate the effectiveness and superiority of the proposed method.Our code is publicly available at http://gffzz188fe103f8f1460asu0bf6b9ucukw6056.ffgz.tsg.suse.edu.cn/XunpengYi/LL-Refiner. 展开更多
关键词 Adaptive refinement low-light image enhancement ultra-high-definition image
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Performance degradation and maintenance optimization strategy of rolling bearings based on data fusion and adaptive partition 认领 引用
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作者 Hong-Chuan Cheng Xin-Hai Li +3 位作者 Guo-Hui Ma Yu Cui Zhi-Wu Shang Xia-Fei Shi 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第2期178-194,共17页
The traditional method of performance degradation prediction and maintenance of rolling bearings only considers a single sensor signal,which makes it difficult to automatically partition degradation stages and prone t... The traditional method of performance degradation prediction and maintenance of rolling bearings only considers a single sensor signal,which makes it difficult to automatically partition degradation stages and prone to over-detection.A new method of performance degradation evaluation and maintenance of rolling bearings based on data-level fusion,adaptive health state partitioning,and state maintenance is proposed.Firstly,considering the degradation and impact in the process of bearing deterioration,the multi-sensor signals are dynamically weighted to achieve data-level fusion.Secondly,a bearing health index was established based on fast spectral correlation,Wasserstein distance,and linear rectification techniques.On this basis,by combining the Bayesian information criterion and the elbow rule,the precise division of rolling bearing health state is realized through hidden Markov model regression.Then,random forest was used to classify and predict the data to verify the validity of the proposed data fusion method and health indicator.Finally,condition-based maintenance strategy based on the fourth moment,stress-strength interference model,and Gamma process is proposed to avoid excessive detection and reduce maintenance costs.Through accelerated degradation experiments and field validation tests on the rolling bearing test data set of Xi’an Jiaotong University and FEMTO(PRONOSTIA),the accuracy and superiority of the proposed method in the prediction and maintenance of bearing health state are verified. 展开更多
关键词 Rolling bearing Data fusion Gamma process Adaptive partition Maintenance strategy
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Analysis of a Mirror-based Assist-as-needed Strategy via Task-performance-based Adaptive Impedance Control 认领 引用
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作者 Qing Sun Qingfeng Li +2 位作者 Xiaolong Yang Shuai Guo Jianwei Niu 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第2期771-782,共12页
Mirror-assisted strategies are commonly used in the rehabilitation training of patients with hemiparesis in the upper limbs following a stroke.Traditional robotic mirror assistance focuses on achieving high-precision ... Mirror-assisted strategies are commonly used in the rehabilitation training of patients with hemiparesis in the upper limbs following a stroke.Traditional robotic mirror assistance focuses on achieving high-precision mirror trajectory tracking,often neglecting the issue of active movement in the affected side.This paper proposes a task performance-based adaptive impedance control,where the robot assists the affected side in an assist-as-needed manner,thereby encouraging the patient to perform active movements.To account for inter-individual variability,a method for assessing the affected side’s motor performance,based on the healthy side’s movement level,is introduced.Adaptive impedance control is then constructed based on the motor performance of the affected side,enabling the robot to provide adaptive assistance force.Eight healthy participants were recruited for experimental testing.Experimental results show that when the robot provides mirror-based assist-as-needed to the affected side,the robot’s stiffness coefficient and assistance force are positively correlated with the motor assessment coefficient of the affected side,thereby verifying the feasibility of the proposed strategy.This study offers a robotic-assisted rehabilitation strategy for stroke patients that balances active participation and individual adaptability,with the potential to enhance rehabilitation outcomes and enable precise rehabilitation interventions. 展开更多
关键词 Bimanual robot Adaptive impedance control Task performance Mirror assistance Assist-as-needed
Interfacial Modulation of Lithium Deposition via an Adaptive Poly(Ether-Thiourea)Protective Layer 认领 引用
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作者 Yongsheng Zhang Xiaolong He +6 位作者 Yinyu Xiang Lieke M.H.Germain Marco Di Michiel Pierre-Olivier Autran Yutao Pei Petra Rudolf Giuseppe Portale 《Carbon Energy》 SCIE EI CAS CSCD 2026年第2期44-58,共15页
Lithium metal is a promising anode material for high-energy-density batteries;however,its practical applications are significantly hindered by unstable lithium deposition and dendrite growth at the solid electrolyte i... Lithium metal is a promising anode material for high-energy-density batteries;however,its practical applications are significantly hindered by unstable lithium deposition and dendrite growth at the solid electrolyte interface.Functional protective coatings on lithium metal surfaces offer a viable solution to these challenges.Herein,an innovative adaptive protective layer for lithium metal anodes based on a thiourea H-bonded supramolecular polymer is developed for the first time.With dense thiourea H-bonding,the lithium bis(trifluoromethanesulfonyl)imide(Li TFSI)incorporated poly(ether-thiourea)protective layer shows strong adhesion to the lithium metal surface and good adaptive properties.The unique viscoelastic and flow characteristics of the poly(ether-thiourea)coating facilitate uniform Li⁺flux,effectively suppressing dendrite formation at the solid electrolyte interface.Furthermore,this innovative polymer integrates in situ generated compounds,such as Li3N and Li2O,significantly enhancing interfacial stability.A comprehensive analysis involving X-ray photoelectron spectroscopy,scanning electron microscopy,X-ray tomography,and COMSOL simulations elucidates the beneficial effects of the adaptive coating.Enhanced performances in Li||Cu,Li||Li,Li||LiFePO4,and Li||S cells demonstrate the effectiveness of the poly(ether-thiourea)coating and its undeniable capability to improve lithium deposition and cycling stability.This study highlights a promising new candidate for developing supramolecular materials capable of stabilizing lithium metal anodes. 展开更多
关键词 adaptive coating cycling stability dendrite growth lithium metal anode protective layer
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Electrospinning-Driven IGZO Nanofiber Phototransistors Bridging Adaptive Processing and Recognition Learning 认领 引用
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作者 Shanshan Jiang Shuo Cheng +3 位作者 Jiawei Yang Xiaohui Guo Bo He Gang He 《Rare Metals》 SCIE EI CAS CSCD 2026年第4期537-548,共12页
The development of neuromorphic electronics with visual perception and adaptive capability is highly desirable for advancing artificial vision systems.Herein,we have demonstrated a dual-plasticity adaptive photo trans... The development of neuromorphic electronics with visual perception and adaptive capability is highly desirable for advancing artificial vision systems.Herein,we have demonstrated a dual-plasticity adaptive photo transistor based on IGZO nanofibers that exhibits the perception and dynamic adaptation behavior of rod and cone cells to varying light environments.Benefiting from the coexistence of oxygen vacancies and trap states in nanofibers,the separation and injection of photogenerated carriers are significantly improved,thereby enabling the light-intensity-dependent dynamic adaptability and the gate-modulated photosensitivity with a narrower adaptation timescale than the bio-systems(<2 min).Moreover,the phototransistor array replicates both photopic and scotopic adaptation,and achieves adaptive contrast enhancement for the overexposed images.Finally,the system enables real-time neuromorphic encoding and recognition of digital signals under varying adaptive processes,and the pattern recognition accuracy is significantly improved from 10%to 95.8%.These results not only demonstrate a facile route for bridging visual sensing,adaptive processing,and neuromorphic computing in a single transistor device but also lay the groundwork for future applications in machine vision and next-generation neuromorphic sensory systems. 展开更多
关键词 adaptive capability IGZO nanofibers neuromorphic computing phototransistor visual perception
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Aerodynamic/control coupling optimization method for reusable vehicles using adaptive partitioning 认领 引用
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作者 Lulu JIANG Xin PAN +2 位作者 Chao DONG Yuan FU Gang CHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第6期340-354,共15页
To address the issues of poor lateral stability,strong interactions between channels,and the inherent trade-offs of global optimization methods in the aerodynamic shape design of reusable hypersonic vehicles,this stud... To address the issues of poor lateral stability,strong interactions between channels,and the inherent trade-offs of global optimization methods in the aerodynamic shape design of reusable hypersonic vehicles,this study proposes an Adaptive Partitioning Optimization(APO)method for aerodynamic/control coupling design.The APO method explicitly integrates the interactions between aerodynamic configuration and longitudinal/lateral control performance,while introducing a variable correlation-based partitioning strategy.This enables multi-channel aerodynamic/control collaborative optimization while avoiding the performance compromises associated with global multidisciplinary optimization.To address the high computational cost of control performance evaluation,a sample augmentation strategy with interpolation correction is introduced,reducing cost while maintaining accuracy.Optimization of a representative reusable vehicle demonstrates that this framework achieves a 2.23%increase in lift-to-drag ratio,a 0.56%reduction in drag coefficient,and enhanced lateral stability.Moreover,it achieves better coordination between aerodynamic and control objectives compared to global optimization.These results highlight the practical value of the APO method in improving aerodynamic and control performance for reusable hypersonic vehicles,offering a scalable and computationally efficient solution for multidisciplinary aerodynamic/control co-design in hypersonic vehicle applications. 展开更多
关键词 Adaptive partitioning Aerodynamic/control coupling Multichannel control Reusable vehicle Shape optimization Small sample interpolation
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Wavelet-based analysis of aeolian sand dynamics and adaptive mitigation strategies for desert highways 认领 引用
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作者 YANG Lingxiang CHENG Jianjun +3 位作者 YAO Bin WANG Yaqiang GAO Li WU Xiao 《Journal of Mountain Science》 SCIE CSCD 2026年第3期1182-1200,共19页
Scientific analysis of aeolian sand environments is fundamental for sustainable disaster mitigation along desert highways.However,significant regional variability in wind energy conditions complicates accurate charact... Scientific analysis of aeolian sand environments is fundamental for sustainable disaster mitigation along desert highways.However,significant regional variability in wind energy conditions complicates accurate characterization of wind regimes and introduces uncertainty in determining optimal monitoring timescales.Moreover,prevailing sand control measures often rely on standardized designs rather than site-specific adaptive strategies.To address these issues,this study proposes an integrated framework for aeolian environment analysis and develops targeted disaster mitigation strategies tailored for desert highways.The proposed framework employs wavelet transform to unravel the periodic characteristics of wind speed time series and integrates multi-source data(including ERA5 wind datasets,sand samples,ASTER GDEM,and multi-temporal remote sensing imagery)to enable a comprehensive aeolian environmental assessment.Concurrently,a suite of adaptive strategies is formulated to mitigate disaster risks along desert highways.Validated through a case study of the Tumushuk-Kunyu Desert Highway in Xinjiang,China,the framework exhibits high accuracy:predictions of annual aeolian sand transport activity show relative errors mostly below 7%against long-term reference sequences,and the calculated resultant drift direction exhibits a strong correlation with observed dune migration,yielding an R-squared value of 0.96.These findings confirm the framework’s reliability and provide a robust basis for designing adaptive,location-specific mitigation strategies,thereby enhancing the sustainability of desert highway infrastructure. 展开更多
关键词 Desert highway Aeolian sand environment Wavelet transform Drift potential Adaptive mitigation measures
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Full-waveform inversion constrained by adaptive sonic logging data within a Bayesian framework 认领 引用
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作者 Jing Wang Qing-Qing Li +2 位作者 Li-Jun Gao Zong-Jie Li Li-Yun Fu 《Petroleum Science》 SCIE EI CAS CSCD 2026年第1期205-219,共15页
The full waveform inversion(FWI)utilizes full wave field data to invert subsurface parameters and is considered one of the most promising data-driven tools for obtaining high precision velocity models.However,the succ... The full waveform inversion(FWI)utilizes full wave field data to invert subsurface parameters and is considered one of the most promising data-driven tools for obtaining high precision velocity models.However,the successful application of FWI in geophysical explo ration remains limited,primarily due to the cycle-skipping issue caused by the absence of low-frequency data,which is one of the main reasons for FWI failures.Incorporating prior regularization constraints FWI can effectively compensate for the lacking low-frequency components and constrain the iterative updates of FWI toward the desired direction,offering a natural advantage in addressing this challenge.However,the weights of the prior information terms are still determined empirically,which introduces significant subjectivity and randomness to the inversion results.To solve this issue,we propose an adaptive method to determine the weight factor based on posterior probability distribution within the Bayesian theoretical framework.This factor adaptively adjusts during each iteration to balance the contributions of the data error term and the prior information term in FWI,which can effectively mitigate the cycle-skipping problem and alleviating the nonlinearity of the inversion process.Numerical examples from the Overthrust model and the Marmousi model show that our method not only enhance the accuracy of FWI,but also demonstrate strong noise resistance. 展开更多
关键词 Full waveform inversion Low-frequency data Sonic logging data Adaptive prior regularization
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Adaptive elite ant colony optimization for track planning in gravity-aided navigation with multi-feature fusion 认领 引用
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作者 Jinbai Zhang Hao Zhou +4 位作者 Yun Xiao Xinshang Li Hong Li Yifeng Chen Zhicai Luo 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第5期112-126,共15页
Autonomous Underwater Vehicle track planning is critical for maritime defense missions,particularly in signal-denied and stealth-sensitive environments.Gravity-aided inertial navigation systems(GAINS),as a passive and... Autonomous Underwater Vehicle track planning is critical for maritime defense missions,particularly in signal-denied and stealth-sensitive environments.Gravity-aided inertial navigation systems(GAINS),as a passive and emission-free approach,offer strong potential for such missions.However,track planning under gravity constraints remains underexplored.This paper proposes an Adaptive Elite Ant Colony Optimization(AEACO)algorithm to address this gap.AEACO integrates two key strategies:an elite reinforcement mechanism inspired by genetic algorithms and a dynamic parameter adjustment method for pheromone-related variables.A gravity adaptability model is first established using fuzzy statistics and entropy-weighted feature fusion to identify navigable regions.AEACO then reinforces elite path segments and self-adjusts its parameters in response to gravity field variations.Experiments across 22real-world marine gravity scenarios show that AEACO consistently outperforms various classical methods.Specifically,it achieves up to 19%shorter paths,40%fewer turns,and 95%faster convergence.Unlike other Ant Colony Optimization(ACO)variants,AEACO operates without fixed parameters or external tuning,making it scalable and adaptable for real-time defense operations in complex underwater environments. 展开更多
关键词 Ant colony optimization Elite strategy Gravity-aided inertial navigation Track planning Gravity adaptive regions
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Adaptive iterative learning control for impact load cyclic fatigue simulator of aircraft 认领 引用
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作者 Shuai WU Sheng SHU +2 位作者 Renjie LI Yaoxing SHANG Zongxia JIAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第3期643-652,共10页
The aircrafts have many structural components that withstand repeated impact loads,which may accumulate fatigue and potentially cause major accidents.To simulate repeated impact loads,it is imperative to design an imp... The aircrafts have many structural components that withstand repeated impact loads,which may accumulate fatigue and potentially cause major accidents.To simulate repeated impact loads,it is imperative to design an impact load cyclic fatigue simulator that applies repeated impact loads to structural components,such as landing gears.Furthermore,the impact load simulator must simulate various loads,and the identical set of parameters employed in conventional controllers are challenging to apply to varying operational conditions.Consequently,the controller must possess learning and adaptive capabilities.Based on the characteristics of repeated impact loads,an Adaptive Iterative Learning Control(AILC)based on the backstepping method is developed in this study.This AILC comprises backstepping control law,parameter adaptation law,iterative learning law,and robust dynamical control term.The adaptation law is not only utilized to estimate unknown system parameters,but also for online identification of system parameters.The iterative learning law can be utilized to learn the characteristics of the system under repeated operating conditions.The robust dynamical control term ensures the stability of the entire system.The experimental results indicate that the AILC can achieve tracking error convergence within a finite time and effectively achieve high-precision torque command tracking. 展开更多
关键词 Adaptive control Iterative learning control Load simulator Repeated impact load Robust dynamical control
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Adaptive fixed-time fuzzy fault-tolerant cooperative spiral-diving guidance law with initial state-independent prescribed performance 认领 引用
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作者 Tianyi WU Zheng WANG +2 位作者 Caisheng WEI Xin NING Zhansheng CHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第5期483-503,共21页
This paper proposes a novel performance guaranteed fixed-time fuzzy adaptive faulttolerant cooperative spiral-diving guidance law for a group of flight vehicles subject to system internal uncertainties,actuator faults... This paper proposes a novel performance guaranteed fixed-time fuzzy adaptive faulttolerant cooperative spiral-diving guidance law for a group of flight vehicles subject to system internal uncertainties,actuator faults,and external disturbances simultaneously.Firstly,based on the analysis of the spiral-diving terminal guidance process,a novel set of guidance dynamic equations,which is different from the traditional line-of-sight angle equations but suitable for the design of a cooperative spiral guidance law,is established.Thereafter,by designing a novel Initial StateIndependent Fixed-Time Prescribed Performance Function(ISIFTPPF),the time-to-go free virtual guidance law that can ensure prescribed performance in spite of any initial condition is developed to generate spiral maneuvers.Subsequently,the fixed-time adaptive guidance law based on the auxiliary subsystem is designed,ensuring that actuator saturation constraints can be satisfied and the unknown disturbances as well as actuator faults can be effectively handled.It should be noted that the proposed method is a low-complexity hierarchical spiral guidance scheme that can remarkably reduce the consumption of computational resources.Theoretical analysis illustrates that the closedloop system is practically fixed-time stable,and the tracking errors will converge within the pregiven boundaries.Finally,the effectiveness,superiority,and practical application potential of the proposed cooperative guidance method are demonstrated by several numerical simulations. 展开更多
关键词 Adaptive fuzzy faulttolerant Cooperative guidance Multiple constraints Multiple flight vehicles Practical fixed-time stability Spiral trajectories
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Bioinspired Auxetic Metastructures Enable Biomechanically Adaptive,Machine Learning‑Enhanced Self‑Powered Sensing with Ultrahigh Efficiency 认领 引用
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作者 Wei Wang Xuechuan Wang +7 位作者 Linbin Li Yi Zhou Wenlong Zhang Long Xing Long Xie Yitong Wang Ouyang Yue Xinhua Liu 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第8期751-768,共18页
Self-powered flexible sensors exhibit revolutionary potential in next-generation wearable technologies owing to their exceptional sensitivity and self-sustaining energy harvesting capabilities.Nevertheless,their wides... Self-powered flexible sensors exhibit revolutionary potential in next-generation wearable technologies owing to their exceptional sensitivity and self-sustaining energy harvesting capabilities.Nevertheless,their widespread deployment remains constrained by three fundamental challenges:dynamic mechanical mismatch between biological tissues and rigid devices,suboptimal energy conversion efficiency,and interfacial impedance fluctuation under deformation.Drawing inspiration from the unique negative Poisson’s ratio mesh architecture of lacewing wings,we present a bioinspired auxetic metastructure-engineered triboelectric nanogenerator.This innovative design integrates engineered collagen and micropatterned fluorinated ethylene propylene as triboelectric layers,unified by an auxetic framework with re-entrant hexagonal unit cells interconnected via triangular ligaments.The metastructure enables exceptional lateral expansion under longitudinal strain while simultaneously enhancing structural rigidity and deformation adaptability.This dual functionality effectively minimizes tissue-device mechanical mismatch,thereby significantly improving signal fidelity,sensitivity,and mechanical-to-electrical conversion efficiency during multi-axial deformations.The optimized device achieves remarkable performance metrics,delivering 478 V output voltage with 13.8%energy conversion efficiency in linear configuration,while demonstrating threefold enhanced stability(58 V,7.58%efficiency)under complex bending compared to conventional designs.Integrated with a convolutional neural network-based machine learning enables exceptional classification accuracy(>99%)across diverse material recognition tasks,validating its robustness as a next-generation platform for adaptive self-powered wearable sensing. 展开更多
关键词 Tissue-device matching Adaptive self-powered sensors Auxetic effect Energy conversion efficiency Neural network model
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Millimeter wave imaging of Range Migration Algorithm with adaptive background filtering 认领 引用
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作者 CHENG Zhi-Hua ZHOU Ran +3 位作者 WANG Meng YU Tao WANG Yu-Lan YAO Jian-Quan 《红外与毫米波学报》 SCIE EI CAS CSCD 北大核心 2026年第2期279-284,共6页
This paper proposes a novel Range Migration Algorithm(RMA)integrated with an adaptive background filtering method specifically designed for near-field millimeter-wave imaging scenarios where targets are in close proxi... This paper proposes a novel Range Migration Algorithm(RMA)integrated with an adaptive background filtering method specifically designed for near-field millimeter-wave imaging scenarios where targets are in close proximity to background structures.This method simulates the attention distribution mode of the human visual system which is used in Artificial Intelligence(AI)and called the Attention Mechanism.Based on the concept of static clutter filtering,the frequency-domain signals of the scanning aperture are divided into grid cells.Background scattering functions are established by analyzing the motion processes within each cell,and the background interference is linearly filtered out.An analysis of the manifestation of background scattering interference within the algorithm is carried out,and the impact of the grid cell dimension on the imaging quality is investigated.Experimental results show that the proposed method exhibits the capability to enhance the signal-to-noise ratio of both the target and the background.It effectively suppresses the background interference,leading to a more prominent image,meanwhile without imposing the excessive computational load.The method offers a novel solution for improving the performance of millimeter-wave imaging technology in practical applications. 展开更多
关键词 information processing technology millimeter-wave imaging Range Migration Algorithm(RMA) attention mechanism adaptive background filtering
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PASSIVITY-BASED SYNCHRONIZATION OF MARKOVIAN JUMP INERTIAL NEURAL NETWORKS VIA ADAPTIVE EVENT-DRIVEN PROTOCOL AND ITS APPLICATION TO IMAGE ENCRYPTION 认领 引用
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作者 A.CHANDRASEKAR Quanxin ZHU +2 位作者 T.RADHIKA M.KAMALI A.R.SUBHASHRI 《Acta Mathematica Scientia》 SCIE CSCD 2026年第3期1555-1580,共26页
This paper concentrates on the study of passivity-based synchronization of inertial neural networks including Markov jump parameters.The second-order differential equations are converted into first-order differential ... This paper concentrates on the study of passivity-based synchronization of inertial neural networks including Markov jump parameters.The second-order differential equations are converted into first-order differential equations using the variable transformation method.To make effective use of network bandwidth resources and to optimize the Markov jump inertial neural networks(MJINNs)performance,an adaptive event-driven protocol controller is studied.To achieve synchronization,an appropriate Lyapunov-Krasovskii functional(LKF)is constructed,which includes double integral terms that capture the information of time-varying delay terms.Some sufficient conditions are obtained in terms of linear matrix inequalities(LMIs)using Reciprocal convex combination lemma(RCCL).Then,a numerical simulation and an application of image encryption are carried out to illustrate the effectiveness of the proposed method. 展开更多
关键词 inertial neural networks adaptive event-driven protocol Markovian jump process synchronization
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Adaptive defect passivation of perovskite solar cells with 2-mercaptoethylammonium chloride advancing over 2000 h photothermal stability 认领 引用
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作者 Natalia N.Udalova Elizaveta M.Nemygina +5 位作者 Nikita N.Chertorizhskiy Andrei S.Tutantsev Wang Chengyuan Nikolai A.Belich Eugene A.Goodilin Alexey B.Tarasov 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第6期355-364,I0010,共10页
One of the key challenges in advancing perovskite solar cells(PSCs)is the development of effective defect-passivation strategies capable of overcoming the intrinsically limited photothermal stability of hybrid halide ... One of the key challenges in advancing perovskite solar cells(PSCs)is the development of effective defect-passivation strategies capable of overcoming the intrinsically limited photothermal stability of hybrid halide perovskites.Increasing attention is being directed toward“adaptive”passivators that not only suppress the initial defect density but also interact as an effective shuttle with degradation products and external oxidants,thereby enhancing long-term device stability.In this work,focused on enhancing the operational stability of PSCs,we introduce 2-mercaptoethylammonium chloride(MEACl)as a multifunctional,adaptive bulk additive that markedly improves PSCs operational stability through a redoxshuttle mechanism based on the reversible S–H⇄S–S transformation.This mechanism enables MEACl to neutralize both external oxygen and in situ generated degradation species such as I⁰/I2 and Pb⁰.Under the ISOS-L-3 accelerated aging protocol,PSCs incorporating 0.1–0.5 mol.%MEACl exhibit a threefold enhancement in photothermal stability at 85℃and a fourfold improvement at 65℃.These results identify 2-mercaptoethylammonium chloride as a highly promising additive for constructing durable perovskite absorbers and next-generation stable optoelectronic devices. 展开更多
关键词 Hybrid halide perovskites Perovskite solar cells Photothermal stability Defect passivation Adaptive passivation 2-Mercaptoethylammonium chloride Redox-shuttle mechanism
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Risk-Aware Adaptive Federated Learning for Cyber-Secure Edge-AI in Smart Edge-IoT Environments 认领 引用
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作者 Tanveer Ahmad Tahani Alsubait +2 位作者 Amina Salhi Amani Ibraheem Muhammad Asim Saleem 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第5期1439-1461,共23页
The rapid adoption of Edge-AI in smart edge-IoT environments has dramatically led to an augmented vulnerability to cyber risks arising from distributed learning,data heterogeneity,and adversarial manipulation.This pap... The rapid adoption of Edge-AI in smart edge-IoT environments has dramatically led to an augmented vulnerability to cyber risks arising from distributed learning,data heterogeneity,and adversarial manipulation.This paper proposes a new risk-aware adaptive learningmodel that federated Edge-AI systems explicitly simulates cyber risk in the process of local training and global aggregation.The proposed solution combines stochastic optimization and adversarial risk bounding with adaptive gradient correction to develop strong learning in non-IID data distributions and malicious client behavior.Convergence guarantees are defined by the theoretical analysis in the case of limited adversarial perturbations.The proposed framework achieves up to 95%detection accuracy and demonstrates more than 20%improvement in robustness,where robustness is defined as the relative degradation in detection performance under adversarial perturbations.The performance is evaluated against state-of-the-art baselines,including HADA-FL and centralized training on the Edge-IIoTset dataset,with results reported as averages over multiple randomized runs.Furthermore,the model converges within 50 communication rounds,which corresponds to a fixed training horizon rather than an early-stopping criterion.These findings demonstrate the usefulness of risk-sensitive adaptive learning in safe and trustworthy Edge-AI implementation in a new generation edge-IoT environment. 展开更多
关键词 Edge AI federated learning(FL) adaptive learning adversarial robustness distributed optimization
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