As a closed-loop learning control method,repetitive control has been widely used in a variety of areas from appliances to aviation.A repetitive control system features perfect reference tracking and disturbance reject...As a closed-loop learning control method,repetitive control has been widely used in a variety of areas from appliances to aviation.A repetitive control system features perfect reference tracking and disturbance rejection in the steady state for periodic signals with a fixed period.This characteristic is important not only for conventional technologies and conventional industries but also for advanced technologies and emerging industries.This paper first explains the concept of repetitive control from its original idea.Next,it describes the structure of a repetitive controller as an internal model and shows the respective points of continuous-and discrete-time repetitive control.It presents a categorized list of practical applications of repetitive control.Moreover,two concrete applications,namely the control of a robotic manipulator and a rotating system,demonstrate the validity of the method with experimental results.Several current studies in this field are also reviewed,and some challenges and future studies for repetitive control are provided.展开更多
Dear Editor,This letter deals with automatically constructing an OPC UA information model(IM)aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems.Empow...Dear Editor,This letter deals with automatically constructing an OPC UA information model(IM)aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems.Empowered by the large language model(LLM),we propose a novel multi-agent collaborative framework to streamline the end-to-end OPC UA IM modeling process.Each agent is equipped with meticulously engineered prompt templates,augmenting their capacity to execute specific tasks.We conduct modeling experiments using real textual data to demonstrate the effectiveness of the proposed method,improving modeling efficiency and reducing the labor workload.展开更多
In the context of multiple-target tracking and surveillance applications,this paper investigates the challenge of determining the optimal positioning of a single autonomous aerial vehicle or agent equipped with multip...In the context of multiple-target tracking and surveillance applications,this paper investigates the challenge of determining the optimal positioning of a single autonomous aerial vehicle or agent equipped with multiple independently-steerable zooming cameras to effectively monitor a set of targets of interest.Each camera is dedicated to tracking a specific target or cluster of targets.The key innovation of this study,in comparison to existing approaches,lies in incorporating the zooming factor for the onboard cameras into the optimization problem.This enhancement offers greater flexibility during mission execution by allowing the autonomous agent to adjust the focal lengths of the onboard cameras,in exchange for varying real-world distances to the corresponding targets,thereby providing additional degrees of freedom to the optimization problem.The proposed optimization framework aims to strike a balance among various factors,including distance to the targets,verticality of viewpoints,and the required focal length for each camera.The primary focus of this paper is to establish the theoretical groundwork for addressing the non-convex nature of the optimization problem arising from these considerations.To this end,we develop an original convex approximation strategy.The paper also includes simulations of diverse scenarios,featuring varying numbers of onboard tracking cameras and target motion profiles,to validate the effectiveness of the proposed approach.展开更多
This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of sys...This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization phenomenon.The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem.Based upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions.Furthermore,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion.Finally,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.展开更多
This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-trigger...This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.展开更多
Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier ...Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://github.com/YifanLu2000/TIM.展开更多
Dear Editor,In this letter,a novel adaptive control design problem for uncertain nonlinear multi-input-multi-output(MIMO)systems with time-varying full state constraints is proposed,where the considered systems consis...Dear Editor,In this letter,a novel adaptive control design problem for uncertain nonlinear multi-input-multi-output(MIMO)systems with time-varying full state constraints is proposed,where the considered systems consist of various subsystems,and the states of each subsystem are interconnected tightly.It is universally acknowledged that in the existing researches with state constraints,system constraint bounds are always constants or time-varying functions.展开更多
SINCE the 18th century,fossil energy in the form of coal,oil,and natural gas has been used on a large scale.These fossil fuels have provided a vast amount of energy,such as electricity,heat,and gas,for industrial prod...SINCE the 18th century,fossil energy in the form of coal,oil,and natural gas has been used on a large scale.These fossil fuels have provided a vast amount of energy,such as electricity,heat,and gas,for industrial production and have been a major contributor to the development of the world economy[1].展开更多
CHATGPT,one of the leading Large Language Models(LLMs),has acquired linguistic capabilities such as text comprehension and logical reasoning,enabling it to engage in natural conversations with humans.
Dear editor,This letter is concerned with the control of cyber-physical systems(CPSs)in the presence of malicious false data injection(FDI)attacks on actuators.The FDI attacks on actuators may result in faults of actu...Dear editor,This letter is concerned with the control of cyber-physical systems(CPSs)in the presence of malicious false data injection(FDI)attacks on actuators.The FDI attacks on actuators may result in faults of actuators or even the instability of CPSs.To tackle this problem,an unknown input observer(UIO)is proposed to estimate the system states and attack signals.For the aim of suppressing the impact of FDI attacks,a discrete-time sliding mode control(DSMC)algorithm is correspondingly put forward,where its reaching law is constructed based on the n-th order difference of the estimation of attack signals.Finally,two simulation instances are presented to show the effectiveness of the proposed method.展开更多
Dear Editor,In recent years,multi-modal medical image fusion has received widespread attention in the image processing community.However,existing works on medical image fusion methods are mostly devoted to pursuing hi...Dear Editor,In recent years,multi-modal medical image fusion has received widespread attention in the image processing community.However,existing works on medical image fusion methods are mostly devoted to pursuing high performance on visual perception and objective fusion metrics,while ignoring the specific purpose in clinical applications.展开更多
Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different fro...Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the discriminator.Moreover。展开更多
Dear editor,Recently,researchers have obtained many new results about the multi-agent systems(MASs)[1]-[3].In[1],the fixed-time cooperative control(FTCC)algorithm of linear MASs with matched disturbances was proposed....Dear editor,Recently,researchers have obtained many new results about the multi-agent systems(MASs)[1]-[3].In[1],the fixed-time cooperative control(FTCC)algorithm of linear MASs with matched disturbances was proposed.The nonholonomic chained-form dynamics case was considered in[2].In[3],the output tracking problem with data packet dropout was solved for high-order MASs.Moreover,delay frequently occurs because of the non-ideal data transmission[4],and the corresponding FTCC algorithm of MASs with delay was given in[5].展开更多
Change detection(CD)is becoming indispensable for unmanned aerial vehicles(UAVs),especially in the domain of water landing,rescue and search.However,even the most advanced models require large amounts of data for mode...Change detection(CD)is becoming indispensable for unmanned aerial vehicles(UAVs),especially in the domain of water landing,rescue and search.However,even the most advanced models require large amounts of data for model training and testing.Therefore,sufficient labeled images with different imaging conditions are needed.Inspired by computer graphics,we present a cloning method to simulate inland-water scene and collect an auto-labeled simulated dataset.The simulated dataset consists of six challenges to test the effects of dynamic background,weather,and noise on change detection models.Then,we propose an image translation framework that translates simulated images to synthetic images.This framework uses shared parameters(encoder and generator)and 22×22 receptive fields(discriminator)to generate realistic synthetic images as model training sets.The experimental results indicate that:1)different imaging challenges affect the performance of change detection models;2)compared with simulated images,synthetic images can effectively improve the accuracy of supervised models.展开更多
In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate ...In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate in clustering.We propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of noise.Built on this framework,a weighted?2-norm regularization term is presented by weighting mixed noise distribution,thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise.Besides,with the constraint of spatial information,the residual estimation becomes more reliable than that only considering an observed image itself.Supporting experiments on synthetic,medical,and real-world images are conducted.The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers.展开更多
The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic di...The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic discrete time(DDT)methodology.Unlike other analysis methodologies,the DDT methodology is capable of serving the distinct time characteristic and having no constraint conditions.Through analyzing the dynamic characteristics of the weight vector,several convergence conditions are drawn,which are beneficial for its application.The performing computer simulations and real applications demonstrate the correctness of the analysis’s conclusions.展开更多
This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and L_p smoothing constraint, which considers the intrinsic geometric information ...This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and L_p smoothing constraint, which considers the intrinsic geometric information of a data set and produces smooth and stable solutions. The main contributions are as follows: first, graph regularization is added into NMF to discover the hidden semantics and simultaneously respect the intrinsic geometric structure information of a data set. Second,the Lpsmoothing constraint is incorporated into NMF to combine the merits of isotropic(L_2-norm) and anisotropic(L_1-norm)diffusion smoothing, and produces a smooth and more accurate solution to the optimization problem. Finally, the update rules and proof of convergence of GSNMF are given. Experiments on several data sets show that the proposed method outperforms related state-of-the-art methods.展开更多
This paper presents a thorough review of control technologies that have been applied to wastewater treatment processes in the environmental engineering regime in the past four decades. It aims to provide a comprehensi...This paper presents a thorough review of control technologies that have been applied to wastewater treatment processes in the environmental engineering regime in the past four decades. It aims to provide a comprehensive technological review for both water engineering professionals and control specialists, giving rise to a suite of up-to-date pathways to impact this field in light of the classified technology hubs. The assessment was conducted with respect to linear control, linearizing control,nonlinear control, and artificial intelligence-based control. The application domain of each technology hub was summarized into a set of comparative tables for a holistic assessment. Challenges and perspectives were offered to these field engineers to help orient their future endeavor.展开更多
In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and ...In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and input saturation constraints,an adaptive sliding-mode tracking control strategy for an ET is presented. Compared with the existing control strategies for an ET, input saturation constraints and parameter uncertainties are adequately considered in the proposed control strategy. At first, the nonlinear dynamic model for control of an ET is described. According to the dynamical model, the nonlinear adaptive sliding-mode tracking control method is presented,where parameter adaptive laws and auxiliary design system are employed. Parameter adaptive law is given to estimate the unknown parameter with an ET. An auxiliary system is designed,and its state is utilized in the tracking control method to handle the input saturation. Stability proof and analysis of the adaptive sliding-mode control method is performed by using Lyapunov stability theory. Finally, the reliability and feasibility of the proposed control strategy are evaluated by computer simulation.Simulation research shows that the proposed sliding-mode control strategy can provide good control performance for an ET.展开更多
This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State estimation for nonlinear systems has been a challenge encountered in a wide range of engineering fields, attracting decades o...This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State estimation for nonlinear systems has been a challenge encountered in a wide range of engineering fields, attracting decades of research effort. To date,one of the most promising and popular approaches is to view and address the problem from a Bayesian probabilistic perspective,which enables estimation of the unknown state variables by tracking their probabilistic distribution or statistics(e.g., mean and covariance) conditioned on a system's measurement data.This article offers a systematic introduction to the Bayesian state estimation framework and reviews various Kalman filtering(KF)techniques, progressively from the standard KF for linear systems to extended KF, unscented KF and ensemble KF for nonlinear systems. It also overviews other prominent or emerging Bayesian estimation methods including Gaussian filtering, Gaussian-sum filtering, particle filtering and moving horizon estimation and extends the discussion of state estimation to more complicated problems such as simultaneous state and parameter/input estimation.展开更多
基金supported in part by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research(B)(23K25252,24K03325)the National Natural Science Foundation of China(61873348)the Natural Science Foundation of Hubei Province,China(2020CFA031)。
文摘As a closed-loop learning control method,repetitive control has been widely used in a variety of areas from appliances to aviation.A repetitive control system features perfect reference tracking and disturbance rejection in the steady state for periodic signals with a fixed period.This characteristic is important not only for conventional technologies and conventional industries but also for advanced technologies and emerging industries.This paper first explains the concept of repetitive control from its original idea.Next,it describes the structure of a repetitive controller as an internal model and shows the respective points of continuous-and discrete-time repetitive control.It presents a categorized list of practical applications of repetitive control.Moreover,two concrete applications,namely the control of a robotic manipulator and a rotating system,demonstrate the validity of the method with experimental results.Several current studies in this field are also reviewed,and some challenges and future studies for repetitive control are provided.
基金supported supported by the Fundamental Research Funds for the Central Universities(226-2024-00004)the National Natural Science Foundation of China(U23 A20326)Key Research and Development Program of Zhejiang Province(2025C01061).
文摘Dear Editor,This letter deals with automatically constructing an OPC UA information model(IM)aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems.Empowered by the large language model(LLM),we propose a novel multi-agent collaborative framework to streamline the end-to-end OPC UA IM modeling process.Each agent is equipped with meticulously engineered prompt templates,augmenting their capacity to execute specific tasks.We conduct modeling experiments using real textual data to demonstrate the effectiveness of the proposed method,improving modeling efficiency and reducing the labor workload.
基金supported by grants PID2022-142946NA-I00 and PID2022-141159OB-I00funded by MICIU/AEI/10.13039/501100011033ERDF/EU
文摘In the context of multiple-target tracking and surveillance applications,this paper investigates the challenge of determining the optimal positioning of a single autonomous aerial vehicle or agent equipped with multiple independently-steerable zooming cameras to effectively monitor a set of targets of interest.Each camera is dedicated to tracking a specific target or cluster of targets.The key innovation of this study,in comparison to existing approaches,lies in incorporating the zooming factor for the onboard cameras into the optimization problem.This enhancement offers greater flexibility during mission execution by allowing the autonomous agent to adjust the focal lengths of the onboard cameras,in exchange for varying real-world distances to the corresponding targets,thereby providing additional degrees of freedom to the optimization problem.The proposed optimization framework aims to strike a balance among various factors,including distance to the targets,verticality of viewpoints,and the required focal length for each camera.The primary focus of this paper is to establish the theoretical groundwork for addressing the non-convex nature of the optimization problem arising from these considerations.To this end,we develop an original convex approximation strategy.The paper also includes simulations of diverse scenarios,featuring varying numbers of onboard tracking cameras and target motion profiles,to validate the effectiveness of the proposed approach.
基金supported in part by the National Science Fund for Excellent Young Scholars of China(62222317)the National Science Foundation of China(62303492)+3 种基金the Major Science and Technology Projects in Hunan Province(2021GK1030)the Science and Technology Innovation Program of Hunan Province(2022WZ1001)the Key Research and Development Program of Hunan Province(2023GK2023)the Fundamental Research Funds for the Central Universities of Central South University(2024ZZTS0116)。
文摘This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization phenomenon.The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem.Based upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions.Furthermore,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion.Finally,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.
基金the Research Grants Council of Hong Kong(CityU 21208921)the Chow Sang Sang Group Research Fund Sponsored by Chow Sang Sang Holdings International Ltd.
文摘This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.
基金supported by the National Natural Science Foundation of China (62276192)。
文摘Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://github.com/YifanLu2000/TIM.
基金supported in part by the National Natural Science Foundation of China(62025303,62173173)。
文摘Dear Editor,In this letter,a novel adaptive control design problem for uncertain nonlinear multi-input-multi-output(MIMO)systems with time-varying full state constraints is proposed,where the considered systems consist of various subsystems,and the states of each subsystem are interconnected tightly.It is universally acknowledged that in the existing researches with state constraints,system constraint bounds are always constants or time-varying functions.
基金supported by the National Natural Science Foundation of China(NSFC)(61821004)。
文摘SINCE the 18th century,fossil energy in the form of coal,oil,and natural gas has been used on a large scale.These fossil fuels have provided a vast amount of energy,such as electricity,heat,and gas,for industrial production and have been a major contributor to the development of the world economy[1].
基金supported in part by the Skywork Intelligence Culture and Technology LTDthe Science and Technology Development Fund,Macao Special Administrative Region(SAR)(0050/2020/A1)the National Natural Science Foundation of China(61533019)。
文摘CHATGPT,one of the leading Large Language Models(LLMs),has acquired linguistic capabilities such as text comprehension and logical reasoning,enabling it to engage in natural conversations with humans.
基金supported in part by the National Natural Science Funds of China(61973277,62073292)the Zhejiang Provincial Natural Science Foundation of China(LR20F030004,LY20F020030)。
文摘Dear editor,This letter is concerned with the control of cyber-physical systems(CPSs)in the presence of malicious false data injection(FDI)attacks on actuators.The FDI attacks on actuators may result in faults of actuators or even the instability of CPSs.To tackle this problem,an unknown input observer(UIO)is proposed to estimate the system states and attack signals.For the aim of suppressing the impact of FDI attacks,a discrete-time sliding mode control(DSMC)algorithm is correspondingly put forward,where its reaching law is constructed based on the n-th order difference of the estimation of attack signals.Finally,two simulation instances are presented to show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62176081,61922075,62171176)the Fundamental Research Funds for the Central Universities(JZ2020HGPA0111,JZ2021HGPA0061)the USTC Research Funds of the Double First-Class Initiative(KY2100000123)。
文摘Dear Editor,In recent years,multi-modal medical image fusion has received widespread attention in the image processing community.However,existing works on medical image fusion methods are mostly devoted to pursuing high performance on visual perception and objective fusion metrics,while ignoring the specific purpose in clinical applications.
基金the National Natural Science Foundation of China(62073304,41977242,61973283)。
文摘Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the discriminator.Moreover。
基金supported in part by the National Natural Science Foundation of China(62103099,61921004)the Natural Science Foundation of Jiangsu Province of China(BK20210214).
文摘Dear editor,Recently,researchers have obtained many new results about the multi-agent systems(MASs)[1]-[3].In[1],the fixed-time cooperative control(FTCC)algorithm of linear MASs with matched disturbances was proposed.The nonholonomic chained-form dynamics case was considered in[2].In[3],the output tracking problem with data packet dropout was solved for high-order MASs.Moreover,delay frequently occurs because of the non-ideal data transmission[4],and the corresponding FTCC algorithm of MASs with delay was given in[5].
基金supported in part by the Science and Technology Innovation 2030-Key Project of“New Generation Artificial Intelligence”(2018AAA0102303)the Young Elite Scientists Sponsorship Program of China Association of Science and Technology(YESS20210289)+1 种基金the China Postdoctoral Science Foundation(2020TQ1057,2020M682823)the National Natural Science Foundation of China(U20B2071,U1913602,91948204)。
文摘Change detection(CD)is becoming indispensable for unmanned aerial vehicles(UAVs),especially in the domain of water landing,rescue and search.However,even the most advanced models require large amounts of data for model training and testing.Therefore,sufficient labeled images with different imaging conditions are needed.Inspired by computer graphics,we present a cloning method to simulate inland-water scene and collect an auto-labeled simulated dataset.The simulated dataset consists of six challenges to test the effects of dynamic background,weather,and noise on change detection models.Then,we propose an image translation framework that translates simulated images to synthetic images.This framework uses shared parameters(encoder and generator)and 22×22 receptive fields(discriminator)to generate realistic synthetic images as model training sets.The experimental results indicate that:1)different imaging challenges affect the performance of change detection models;2)compared with simulated images,synthetic images can effectively improve the accuracy of supervised models.
基金supported in part by the Doctoral Students’Short Term Study Abroad Scholarship Fund of Xidian Universitythe National Natural Science Foundation of China(61873342,61672400,62076189)+1 种基金the Recruitment Program of Global Expertsthe Science and Technology Development Fund,MSAR(0012/2019/A1)。
文摘In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate in clustering.We propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of noise.Built on this framework,a weighted?2-norm regularization term is presented by weighting mixed noise distribution,thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise.Besides,with the constraint of spatial information,the residual estimation becomes more reliable than that only considering an observed image itself.Supporting experiments on synthetic,medical,and real-world images are conducted.The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers.
基金supported by the National Natural Science Foundation of China(61903375,61673387,61374120)Shaanxi Province Natural Science Foundation(2016JM6015)。
文摘The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic discrete time(DDT)methodology.Unlike other analysis methodologies,the DDT methodology is capable of serving the distinct time characteristic and having no constraint conditions.Through analyzing the dynamic characteristics of the weight vector,several convergence conditions are drawn,which are beneficial for its application.The performing computer simulations and real applications demonstrate the correctness of the analysis’s conclusions.
基金supported by the National Natural Science Foundation of China(61702251,61363049,11571011)the State Scholarship Fund of China Scholarship Council(CSC)(201708360040)+3 种基金the Natural Science Foundation of Jiangxi Province(20161BAB212033)the Natural Science Basic Research Plan in Shaanxi Province of China(2018JM6030)the Doctor Scientific Research Starting Foundation of Northwest University(338050050)Youth Academic Talent Support Program of Northwest University
文摘This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and L_p smoothing constraint, which considers the intrinsic geometric information of a data set and produces smooth and stable solutions. The main contributions are as follows: first, graph regularization is added into NMF to discover the hidden semantics and simultaneously respect the intrinsic geometric structure information of a data set. Second,the Lpsmoothing constraint is incorporated into NMF to combine the merits of isotropic(L_2-norm) and anisotropic(L_1-norm)diffusion smoothing, and produces a smooth and more accurate solution to the optimization problem. Finally, the update rules and proof of convergence of GSNMF are given. Experiments on several data sets show that the proposed method outperforms related state-of-the-art methods.
基金supported by the Fulbright Visiting Scholar Program from the Department of State in the U.S.
文摘This paper presents a thorough review of control technologies that have been applied to wastewater treatment processes in the environmental engineering regime in the past four decades. It aims to provide a comprehensive technological review for both water engineering professionals and control specialists, giving rise to a suite of up-to-date pathways to impact this field in light of the classified technology hubs. The assessment was conducted with respect to linear control, linearizing control,nonlinear control, and artificial intelligence-based control. The application domain of each technology hub was summarized into a set of comparative tables for a holistic assessment. Challenges and perspectives were offered to these field engineers to help orient their future endeavor.
基金partially supported by the National Natural Science Foundation of China(61773189)Natural Science Fundamental of Liaoning Province(20170540443)the Program for Liaoning Innovative Research Team in University(LT2016006)
文摘In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and input saturation constraints,an adaptive sliding-mode tracking control strategy for an ET is presented. Compared with the existing control strategies for an ET, input saturation constraints and parameter uncertainties are adequately considered in the proposed control strategy. At first, the nonlinear dynamic model for control of an ET is described. According to the dynamical model, the nonlinear adaptive sliding-mode tracking control method is presented,where parameter adaptive laws and auxiliary design system are employed. Parameter adaptive law is given to estimate the unknown parameter with an ET. An auxiliary system is designed,and its state is utilized in the tracking control method to handle the input saturation. Stability proof and analysis of the adaptive sliding-mode control method is performed by using Lyapunov stability theory. Finally, the reliability and feasibility of the proposed control strategy are evaluated by computer simulation.Simulation research shows that the proposed sliding-mode control strategy can provide good control performance for an ET.
文摘This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State estimation for nonlinear systems has been a challenge encountered in a wide range of engineering fields, attracting decades of research effort. To date,one of the most promising and popular approaches is to view and address the problem from a Bayesian probabilistic perspective,which enables estimation of the unknown state variables by tracking their probabilistic distribution or statistics(e.g., mean and covariance) conditioned on a system's measurement data.This article offers a systematic introduction to the Bayesian state estimation framework and reviews various Kalman filtering(KF)techniques, progressively from the standard KF for linear systems to extended KF, unscented KF and ensemble KF for nonlinear systems. It also overviews other prominent or emerging Bayesian estimation methods including Gaussian filtering, Gaussian-sum filtering, particle filtering and moving horizon estimation and extends the discussion of state estimation to more complicated problems such as simultaneous state and parameter/input estimation.
