This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the ...Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the fish’s behavior,health,and environmental adaptability.However,when multi-object tracking(MOT)algorithms are applied to the high-density aquaculture environment,occlusion and overlapping among fish may result in missed detections,false detections,and identity switching problems,which limit the tracking accuracy.To address these issues,this paper proposes FishTracker,a MOT algorithm,by utilizing a Tracking-by-Detection framework.First,the neck part of the YOLOv8 model is enhanced by introducing a Multi-Scale Dilated Attention(MSDA)module to improve object localization and classification confidence.Second,an Adaptive Kalman Filter(AKF)is employed in the tracking phase to dynamically adjust motion prediction parameters,thereby overcoming target adhesion and nonlinear motion in complex scenarios.Experimental results show that FishTracker achieves a multi-object tracking accuracy(MOTA)of 93.22% and 87.24% in bright and dark illumination conditions,respectively.Further validation in a real aquaculture scenario reveal that FishTracker achieves aMOTA of 76.70%,which is 5.34% higher than the baselinemodel.The higher order tracking accuracy(HOTA)reaches 50.5%,which is 3.4% higher than the benchmark.In conclusion,FishTracker can provide reliable technical support for accurate tracking and behavioral analysis of high-density fish populations.展开更多
The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is...The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is proposed to reduce communication load in networked control systems by redesigning existing anti-disturbance DAT algorithms and disturbance observers.Furthermore,a fully distributed event-triggering condition is employed to schedule event times for each agent.Simulation results demonstrate that the proposed ETAD-DAT algorithm is able to achieve accurate average tracking of multiple time-varying reference signals despite the presence of external disturbances,while the communication efficiency can be improved obviously.展开更多
This paper investigates the challenges of structural inconsistency,matching accuracy degradation,and trajectory interruptions caused by high-speed motion,frequent occlusions,and appearance variations of unmanned aeria...This paper investigates the challenges of structural inconsistency,matching accuracy degradation,and trajectory interruptions caused by high-speed motion,frequent occlusions,and appearance variations of unmanned aerial vehicle(UAV) targets in low-altitude airspace.A novel UAV visual tracking method is proposed for dynamic structural distortions,with a focus on structural consistency modeling to improve system robustness in complex scenarios.Unlike prior methods such as STARK,which rely on spatio-temporal prediction,and KeepTrack,which emphasize template maintenance,our approach enforces structural-level consistency between historical and current features,thereby addressing UAV-specific issues of rapid maneuvering and environmental complexity.The proposed framework features a structure-aware architecture that incorporates dual complementary mechanisms serving as spatial completion and temporal restoration components.First,a multi-scale structure extraction module with adaptive anchor scheduling is developed to dynamically perceive spatial target shape and generate high-quality proposals.Second,a structural memory module is designed to reconstruct local regions by leveraging high-confidence historical structural representations,thereby maintaining spatiotemporal coherence across frames.Furthermore,a structural verification mechanism coupled with a meta-learning-driven re-identification strategy is introduced to detect abrupt structural distortions and adaptively update templates,significantly improving resilience against disturbances.Overall,the main contributions of this paper can be summarized as follows:(1) introducing structural consistency modeling into UAV visual tracking for the first time;(2) designing a unified framework that combines adaptive proposal generation,full-image matching,and re-identification under structural constraints;and(3) achieving state-of-the-art performance on the anti-UAV benchmark,highlighting the method's practical value in real-world UAV surveillance applications.展开更多
This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity p...This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model,as the kinematic model cannot accurately characterize the motion characteristics of the robot.Then,by introducing the Lorentz function,the improved iterative linear quadratic regulator(iLQR) method is used to solve the nonlinear MPC(NMPC) controller with constraints.In addition,in order to reduce computational burden,a closed gradient calculation method is introduced to improve algorithm efficiency.Finally,the feasibility and effectiveness of this method are verified through simulation and experiment.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
Great Snipe(Gallinago media) is a shore bird which has a Near Threatened status on the global scale.However,little is known about its migration strategy from the breeding range in Russia.This study is the first one ai...Great Snipe(Gallinago media) is a shore bird which has a Near Threatened status on the global scale.However,little is known about its migration strategy from the breeding range in Russia.This study is the first one aiming to reveal migration routes,stopovers and wintering grounds of adult Great Snipes from their breeding range in Russia using GPS devices.We also analyzed connectivity of Great Snipes from different breeding populations of this species during non-breeding season.In 2021,we equipped seven males and three females with satellite transmitters,ICARUS Basic Tags,in the breeding range in central European Russia(56°75′N,37°65 E).One female appeared later in tundra of north-eastern Europe.In the second half of July to early September,birds migrated to Africa in a fairly wide front and made stopovers in Europe before crossing seas and the Sahara.Our data allowed to suppose high mortality of birds on migration,especially during the trans-Saharan flight.Only four Great Snipes reached Africa alive during southward migration.These birds spread over across wide area from Eritrea to Ghana after the trans-Saharan flight,after which they moved in a general westward direction and made final prolonged stopovers in Ghana or to the south of Chad Lake.In October/December birds relocated to wintering grounds in Sub-Equatorial Afrotropics as far as the south of Democratic Republic of the Congo and Zambia;with intermediate winter sites in low and middle reaches of the Congo Basin.Together with other published results,our data showed wide overlap of African non-breeding grounds of birds coming from lowland Eastern European and mountain Scandinavian breeding populations.The results also indicated insufficient conservation status of migration stopovers and wintering sites,used by Great Snipes,and demonstrated high importance of West Africa for conservation of this species.展开更多
Accurately estimating depth from underwater monocular images is essential for the target tracking task of unmanned underwater vehicles.This work proposes a method based on the Lpg-Lap Unet architecture.First,the Unet ...Accurately estimating depth from underwater monocular images is essential for the target tracking task of unmanned underwater vehicles.This work proposes a method based on the Lpg-Lap Unet architecture.First,the Unet architecture integrates Laplacian pyramid depth residuals and Sobel operators to improve the boundary details in depth images,which may suffer from the feature loss caused by upsampling and the blurriness of underwater images.Multiscale local planar guidance layers then fully exploit the intermediate depth features,and a comprehensive loss function ensures robustness and accuracy.Experimental results on benchmarks demonstrate the effectiveness of Lpg-Lap Unet and its superior performance over state-of-the-art models.An underwater target tracking system is then designed to further validate its real-time capabilities in the AirSim simulation platform.展开更多
This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact ...This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.展开更多
This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Consi...This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.展开更多
Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This stu...Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.展开更多
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
Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and ...Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality.We propose a drift-aware,power-quality-constrained MPPT framework that co-optimizes MPPT,PLL,and current-loop gains under stochastic frequency drift,while enforcing IEEE-519 limits(per-order Ih/IL and TDD)during optimization.Unlike energy-only or THD-only methods,the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting.Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles(Douala/Yaoundé),combining measured-style irradiance/temperature traces,partial-shading patterns,and stochastic frequency drift up to±0.8 Hz with synthetic contingencies.Across a 30-scenario campaign,the proposed controller achievesηMPPT=99.3%–99.6%(vs.98.6%Incremental Conductance and 97.8%Perturb-and-Observe),lowers DC-link ripple by 35%–48%,reduces oscillatory PCC power by≈41%,maintains THD≤2.5%(5%limit)and PF≥0.99,and shortens irradiance-step settling from 85–110 ms to 50–65 ms.Sensitivity to PLL bandwidth shows a broad optimum(≈60–90 Hz)with minimum THD/ripple,and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield.The approach is controller-agnostic,firmware-deployable,and generalizes to other converter-interfaced renewables;we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.展开更多
The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking...The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.展开更多
In practical application,mean shift tracking algorithm is easy to generate tracking drift when the target and the background have similar color distribution.Based on the mean shift algorithm,a kind of background weake...In practical application,mean shift tracking algorithm is easy to generate tracking drift when the target and the background have similar color distribution.Based on the mean shift algorithm,a kind of background weaken weight is proposed in the paper firstly.Combining with the object center weight based on the kernel function,the problem of interference of the similar color background can be solved.And then,a model updating strategy is presented to improve the tracking robustness on the influence of occlusion,illumination,deformation and so on.With the test on the sequence of Tiger,the proposed approach provides better performance than the original mean shift tracking algorithm.展开更多
To solve the mismatch between the candidate model and the reference model caused by the time change of the tracked head, a novel mean shift algorithm based on a fusion model is provided. A fusion model is employed to ...To solve the mismatch between the candidate model and the reference model caused by the time change of the tracked head, a novel mean shift algorithm based on a fusion model is provided. A fusion model is employed to describe the tracked head by sampling the models of the fore-head and the back-head under different situations. Thus the fusion head reference model is represented by the color distribution estimated from both the fore- head and the back-head. The proposed tracking system is efficient and it is easy to realize the goal of continual tracking of the head by using the fusion model. The results show that the new tracker is robust up to a 360°rotation of the head on a cluttered background and the tracking precision is improved.展开更多
The mean shift tracker has difficulty in tracking fast moving targets and suffers from tracking error accumulation problem. To overcome the limitations of the mean shift method, a new approach is proposed by integrati...The mean shift tracker has difficulty in tracking fast moving targets and suffers from tracking error accumulation problem. To overcome the limitations of the mean shift method, a new approach is proposed by integrating the mean shift algorithm and frame-difference methods. The rough position of the moving tar- get is first located by the direct frame-difference algorithm and three-frame-difference algorithm for the immobile camera scenes and mobile camera scenes, respectively. Then, the mean shift algorithm is used to achieve precise tracking of the target. Several tracking experiments show that the proposed method can effectively track first moving targets and overcome the tracking error accumulation problem.展开更多
Directed at the problem of occlusion in target tracking,a new improved algorithm based on the Meanshift algorithm and Kalman filter is proposed.The algorithm effectively combines the Meanshift algorithm with the Kalma...Directed at the problem of occlusion in target tracking,a new improved algorithm based on the Meanshift algorithm and Kalman filter is proposed.The algorithm effectively combines the Meanshift algorithm with the Kalman filtering algorithm to determine the position of the target centroid and subsequently adjust the current search window adaptively according to the target centroid position and the previous frame search window boundary.The derived search window is more closely matched to the location of the target,which improves the accuracy and reliability of tracking.The environmental influence and other influencing factors on the algorithm are also reduced.Through comparison and analysis of the experiments,the modified algorithm demonstrates good stability and adaptability,and can effectively solve the problem of large area occlusion and similar interference.展开更多
The generic Meanshift is susceptible to interference of background pixels with the target pixels in the kernel of the reference model, which compromises the tracking performance. In this paper, we enhance the target c...The generic Meanshift is susceptible to interference of background pixels with the target pixels in the kernel of the reference model, which compromises the tracking performance. In this paper, we enhance the target color feature by attenuating the background color within the kernel through enlarging the pixel weightings which map to the pixels on the target. This way, the background pixel interference is largely suppressed in the color histogram in the course of constructing the target reference model. In addition, the proposed method also reduces the number of Meanshift iterations, which speeds up the algorithmic convergence. The two tests validate the proposed approach with improved tracking robustness on real-world video sequences.展开更多
In order to track ground moving target, a variable structure interacting multiple model （VS-IMM） using mean shift unscented particle filter （MS-UPF） is proposed in this paper. In model-conditioned filtering, sampl...In order to track ground moving target, a variable structure interacting multiple model （VS-IMM） using mean shift unscented particle filter （MS-UPF） is proposed in this paper. In model-conditioned filtering, sample particles obtained from the unscented particle filter are moved towards the maximal posterior density estimation of the target state through mean shift. On the basis of stop model in VS-IMM, hide model is proposed. Once the target is obscured by terrain, the prediction at prior time is used instead of the measurement at posterior time; in addition, the road model set used is not changed. A ground moving target indication （GMTI） radar is employed in three common simulation scenarios of ground target： entering or leaving a road, crossing a junction and no measurement. Two evaluation indexes, root mean square error （RMSE） and average normalized estimation error squared （ANEES）, are used. The results indicate that when the road on which the target moving changes, the tracking accuracy is effectively improved in the proposed algorithm. Moreover, track interruption could be avoided if the target is moving too slowly or masked by terrain.展开更多
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
基金funded by the Fundamental Research Funds for the Central Universities(Grant No.106-YDZX2025022)the Startup Foundation of New Professor at Nanjing Agricultural University(Grant No.106-804005)the“Qing Lan Project”of Jiangsu Higher Education Institutions.
文摘Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the fish’s behavior,health,and environmental adaptability.However,when multi-object tracking(MOT)algorithms are applied to the high-density aquaculture environment,occlusion and overlapping among fish may result in missed detections,false detections,and identity switching problems,which limit the tracking accuracy.To address these issues,this paper proposes FishTracker,a MOT algorithm,by utilizing a Tracking-by-Detection framework.First,the neck part of the YOLOv8 model is enhanced by introducing a Multi-Scale Dilated Attention(MSDA)module to improve object localization and classification confidence.Second,an Adaptive Kalman Filter(AKF)is employed in the tracking phase to dynamically adjust motion prediction parameters,thereby overcoming target adhesion and nonlinear motion in complex scenarios.Experimental results show that FishTracker achieves a multi-object tracking accuracy(MOTA)of 93.22% and 87.24% in bright and dark illumination conditions,respectively.Further validation in a real aquaculture scenario reveal that FishTracker achieves aMOTA of 76.70%,which is 5.34% higher than the baselinemodel.The higher order tracking accuracy(HOTA)reaches 50.5%,which is 3.4% higher than the benchmark.In conclusion,FishTracker can provide reliable technical support for accurate tracking and behavioral analysis of high-density fish populations.
基金part supported by the National Natural Science Foundation(62203034,62273126,62203035)the Ling-Yan Research and Development Project of Zhejiang Province of China(2023C03185)。
文摘The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is proposed to reduce communication load in networked control systems by redesigning existing anti-disturbance DAT algorithms and disturbance observers.Furthermore,a fully distributed event-triggering condition is employed to schedule event times for each agent.Simulation results demonstrate that the proposed ETAD-DAT algorithm is able to achieve accurate average tracking of multiple time-varying reference signals despite the presence of external disturbances,while the communication efficiency can be improved obviously.
基金Supported by the National Science Foundation of China (No.62571164)the Natural Science Foundation of Heilongjiang Province (No.PL2024F025)the Fundamental Scientific Research Funds of Heilongjiang Province (No.2022-KYYWF-1050)。
文摘This paper investigates the challenges of structural inconsistency,matching accuracy degradation,and trajectory interruptions caused by high-speed motion,frequent occlusions,and appearance variations of unmanned aerial vehicle(UAV) targets in low-altitude airspace.A novel UAV visual tracking method is proposed for dynamic structural distortions,with a focus on structural consistency modeling to improve system robustness in complex scenarios.Unlike prior methods such as STARK,which rely on spatio-temporal prediction,and KeepTrack,which emphasize template maintenance,our approach enforces structural-level consistency between historical and current features,thereby addressing UAV-specific issues of rapid maneuvering and environmental complexity.The proposed framework features a structure-aware architecture that incorporates dual complementary mechanisms serving as spatial completion and temporal restoration components.First,a multi-scale structure extraction module with adaptive anchor scheduling is developed to dynamically perceive spatial target shape and generate high-quality proposals.Second,a structural memory module is designed to reconstruct local regions by leveraging high-confidence historical structural representations,thereby maintaining spatiotemporal coherence across frames.Furthermore,a structural verification mechanism coupled with a meta-learning-driven re-identification strategy is introduced to detect abrupt structural distortions and adaptively update templates,significantly improving resilience against disturbances.Overall,the main contributions of this paper can be summarized as follows:(1) introducing structural consistency modeling into UAV visual tracking for the first time;(2) designing a unified framework that combines adaptive proposal generation,full-image matching,and re-identification under structural constraints;and(3) achieving state-of-the-art performance on the anti-UAV benchmark,highlighting the method's practical value in real-world UAV surveillance applications.
基金Supported by the Zhejiang Provincial Natural Science Foundation of China (No.LR23F030002)。
文摘This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model,as the kinematic model cannot accurately characterize the motion characteristics of the robot.Then,by introducing the Lorentz function,the improved iterative linear quadratic regulator(iLQR) method is used to solve the nonlinear MPC(NMPC) controller with constraints.In addition,in order to reduce computational burden,a closed gradient calculation method is introduced to improve algorithm efficiency.Finally,the feasibility and effectiveness of this method are verified through simulation and experiment.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金A support for different activities in the framework of this research was provided by Max Planck Institute of Animal Behavior,the Russian space agency (Roskosmos),German Aerospace Center and Institute for Geography of the Russian Academy of Sciences via International Cooperation for Animal Research Using Space as well as by NABU–The Nature and Biodiversity Conservation Union2021 was carried out as a joint project of Birds Russia and Manfred-Hermsen Stiftung+2 种基金funded under state assignments of the Severtsov Institute of Ecology and Evolution of the Russian Academy of Science (No. 0089-2021-0004, FFER-2024-0013No. 0089-2021-0010, FFER-2024-0022No. 1022040700480-0-1.6.15)。
文摘Great Snipe(Gallinago media) is a shore bird which has a Near Threatened status on the global scale.However,little is known about its migration strategy from the breeding range in Russia.This study is the first one aiming to reveal migration routes,stopovers and wintering grounds of adult Great Snipes from their breeding range in Russia using GPS devices.We also analyzed connectivity of Great Snipes from different breeding populations of this species during non-breeding season.In 2021,we equipped seven males and three females with satellite transmitters,ICARUS Basic Tags,in the breeding range in central European Russia(56°75′N,37°65 E).One female appeared later in tundra of north-eastern Europe.In the second half of July to early September,birds migrated to Africa in a fairly wide front and made stopovers in Europe before crossing seas and the Sahara.Our data allowed to suppose high mortality of birds on migration,especially during the trans-Saharan flight.Only four Great Snipes reached Africa alive during southward migration.These birds spread over across wide area from Eritrea to Ghana after the trans-Saharan flight,after which they moved in a general westward direction and made final prolonged stopovers in Ghana or to the south of Chad Lake.In October/December birds relocated to wintering grounds in Sub-Equatorial Afrotropics as far as the south of Democratic Republic of the Congo and Zambia;with intermediate winter sites in low and middle reaches of the Congo Basin.Together with other published results,our data showed wide overlap of African non-breeding grounds of birds coming from lowland Eastern European and mountain Scandinavian breeding populations.The results also indicated insufficient conservation status of migration stopovers and wintering sites,used by Great Snipes,and demonstrated high importance of West Africa for conservation of this species.
基金partially supported by the Natural Science Foundation of Shandong Province,China(No.ZR2023ME009)the National Natural Science Foundation of China(No.51909252)。
文摘Accurately estimating depth from underwater monocular images is essential for the target tracking task of unmanned underwater vehicles.This work proposes a method based on the Lpg-Lap Unet architecture.First,the Unet architecture integrates Laplacian pyramid depth residuals and Sobel operators to improve the boundary details in depth images,which may suffer from the feature loss caused by upsampling and the blurriness of underwater images.Multiscale local planar guidance layers then fully exploit the intermediate depth features,and a comprehensive loss function ensures robustness and accuracy.Experimental results on benchmarks demonstrate the effectiveness of Lpg-Lap Unet and its superior performance over state-of-the-art models.An underwater target tracking system is then designed to further validate its real-time capabilities in the AirSim simulation platform.
基金supported by National Natural Science Foundation of China[grant number 62173208]Taishan Scholar Project of Shandong Province of China[grant number tsqn202103061]。
文摘This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.
基金supported by the National Natural Science Foundation of China(62333011,62020106003)the Natural Science Foundation of Jiangsu Province of China(BK20222012)+1 种基金the Fundamental Research Funds for the Central Universities(NE2024005)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0594)。
文摘This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.
基金supported by the Malaysia Ministry of Higher Education under Fundamental Research Grant Scheme with Project Code:FRGS/1/2024/TK07/USM/02/3.
文摘Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.
基金supported by the National Natural Science Foundation of China(U24B20183)the Pioneer Leading Goose+X Science and Technology Program of Zhejiang Province(2025C02018)。
文摘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.
基金Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project(Grant No.RGP2/587/46).
文摘Photovoltaic(PV)systems in the field operate under complex,uncertain conditions rapid irradiance ramps,partial shading,temperature swings,surface soiling,and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality.We propose a drift-aware,power-quality-constrained MPPT framework that co-optimizes MPPT,PLL,and current-loop gains under stochastic frequency drift,while enforcing IEEE-519 limits(per-order Ih/IL and TDD)during optimization.Unlike energy-only or THD-only methods,the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting.Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles(Douala/Yaoundé),combining measured-style irradiance/temperature traces,partial-shading patterns,and stochastic frequency drift up to±0.8 Hz with synthetic contingencies.Across a 30-scenario campaign,the proposed controller achievesηMPPT=99.3%–99.6%(vs.98.6%Incremental Conductance and 97.8%Perturb-and-Observe),lowers DC-link ripple by 35%–48%,reduces oscillatory PCC power by≈41%,maintains THD≤2.5%(5%limit)and PF≥0.99,and shortens irradiance-step settling from 85–110 ms to 50–65 ms.Sensitivity to PLL bandwidth shows a broad optimum(≈60–90 Hz)with minimum THD/ripple,and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield.The approach is controller-agnostic,firmware-deployable,and generalizes to other converter-interfaced renewables;we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.
基金The National Natural Science Foundation of China(No60672094)
文摘The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.
基金National Natural Science Foundation of China(No.61201412)
文摘In practical application,mean shift tracking algorithm is easy to generate tracking drift when the target and the background have similar color distribution.Based on the mean shift algorithm,a kind of background weaken weight is proposed in the paper firstly.Combining with the object center weight based on the kernel function,the problem of interference of the similar color background can be solved.And then,a model updating strategy is presented to improve the tracking robustness on the influence of occlusion,illumination,deformation and so on.With the test on the sequence of Tiger,the proposed approach provides better performance than the original mean shift tracking algorithm.
基金The National Natural Science Foundation of China(No.60672094,60673188,U0735004)the National High Technology Research and Development Program of China(863 Program)(No.2008AA01Z303)the National Basic Research Program of China (973 Program)(No.2009CB320804)
文摘To solve the mismatch between the candidate model and the reference model caused by the time change of the tracked head, a novel mean shift algorithm based on a fusion model is provided. A fusion model is employed to describe the tracked head by sampling the models of the fore-head and the back-head under different situations. Thus the fusion head reference model is represented by the color distribution estimated from both the fore- head and the back-head. The proposed tracking system is efficient and it is easy to realize the goal of continual tracking of the head by using the fusion model. The results show that the new tracker is robust up to a 360°rotation of the head on a cluttered background and the tracking precision is improved.
基金supported by the Fundamental Research Funds for the Central Universities Project(CDJZR10170010)
文摘The mean shift tracker has difficulty in tracking fast moving targets and suffers from tracking error accumulation problem. To overcome the limitations of the mean shift method, a new approach is proposed by integrating the mean shift algorithm and frame-difference methods. The rough position of the moving tar- get is first located by the direct frame-difference algorithm and three-frame-difference algorithm for the immobile camera scenes and mobile camera scenes, respectively. Then, the mean shift algorithm is used to achieve precise tracking of the target. Several tracking experiments show that the proposed method can effectively track first moving targets and overcome the tracking error accumulation problem.
基金Supported by the Scholarship of China Scholarship Council(CSC)(201606935043)
文摘Directed at the problem of occlusion in target tracking,a new improved algorithm based on the Meanshift algorithm and Kalman filter is proposed.The algorithm effectively combines the Meanshift algorithm with the Kalman filtering algorithm to determine the position of the target centroid and subsequently adjust the current search window adaptively according to the target centroid position and the previous frame search window boundary.The derived search window is more closely matched to the location of the target,which improves the accuracy and reliability of tracking.The environmental influence and other influencing factors on the algorithm are also reduced.Through comparison and analysis of the experiments,the modified algorithm demonstrates good stability and adaptability,and can effectively solve the problem of large area occlusion and similar interference.
基金Supported by the Program for Technology Innovation Team of Ningbo Government (No. 2011B81002)the Ningbo University Science Research Foundation (No.xkl11075)
文摘The generic Meanshift is susceptible to interference of background pixels with the target pixels in the kernel of the reference model, which compromises the tracking performance. In this paper, we enhance the target color feature by attenuating the background color within the kernel through enlarging the pixel weightings which map to the pixels on the target. This way, the background pixel interference is largely suppressed in the color histogram in the course of constructing the target reference model. In addition, the proposed method also reduces the number of Meanshift iterations, which speeds up the algorithmic convergence. The two tests validate the proposed approach with improved tracking robustness on real-world video sequences.
文摘In order to track ground moving target, a variable structure interacting multiple model （VS-IMM） using mean shift unscented particle filter （MS-UPF） is proposed in this paper. In model-conditioned filtering, sample particles obtained from the unscented particle filter are moved towards the maximal posterior density estimation of the target state through mean shift. On the basis of stop model in VS-IMM, hide model is proposed. Once the target is obscured by terrain, the prediction at prior time is used instead of the measurement at posterior time; in addition, the road model set used is not changed. A ground moving target indication （GMTI） radar is employed in three common simulation scenarios of ground target： entering or leaving a road, crossing a junction and no measurement. Two evaluation indexes, root mean square error （RMSE） and average normalized estimation error squared （ANEES）, are used. The results indicate that when the road on which the target moving changes, the tracking accuracy is effectively improved in the proposed algorithm. Moreover, track interruption could be avoided if the target is moving too slowly or masked by terrain.
