期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到320篇文章
< 1 2 … 16 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
State estimation improvement in strongly coupled data assimilation with a two-scale Lorenz model 认领 引用
1
作者 Yanqiu Gao Shaoting Ge +2 位作者 Jicai Zhang Yiting Wang Qun He 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2026年第1期176-189,共14页
Coupled data assimilation(CDA)is a powerful strategy for integrating observations with coupled numerical models.This strategy holds great potential for enhancing weather and climate reanalysis and prediction.How to ad... Coupled data assimilation(CDA)is a powerful strategy for integrating observations with coupled numerical models.This strategy holds great potential for enhancing weather and climate reanalysis and prediction.How to address crossscale interactions in CDA is an important issue.In particular,the cross-scale interactions in the strongly coupled data assimilation(SCDA)framework pose substantial challenges.In this study,increasing the state estimation accuracy using an ensemble adjustment Kalman filter based on the two-scale Lorenz’96(tsL96)model is investigated.Using the SCDA framework,we adopt cross-component localization factors and several covariance inflation schemes to address the filter divergence problem.The results show that ensembles of an appropriate size can achieve good assimilation results,the optimal localization parameters are scale-dependent for the model variables,and the adaptive inflation scheme outperforms the static fixed and relaxation-to-prior spread schemes.Although these experiments were carried out using an ideal framework,this study provides a valuable reference for improving estimation accuracy with the SCDA framework in operational simulation and prediction models. 展开更多
关键词 state estimation ensemble adjustment Kalman filter strongly coupled data assimilation multiple-scale
暂未订购 下载PDF
State Estimation With Model Uncertainty Using Structure Variational Bayesian and Transfer Learning 认领 引用
2
作者 Shuang Gao Xiaoli Luan +2 位作者 Biao Huang Shunyi Zhao Fei Liu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第3期715-727,共13页
This paper proposes a novel approach to address parameter uncertainties for state estimation in Markovian jump linear systems by leveraging transfer learning.Assume that the source domain model is available and reliab... This paper proposes a novel approach to address parameter uncertainties for state estimation in Markovian jump linear systems by leveraging transfer learning.Assume that the source domain model is available and reliable,and the target domain model has significant model parameter uncertainties.To enhance estimation performance in the target domain,the proposed method transfers model knowledge from the source domain and adjusts it using a tuning factor before incorporating it into the target domain estimator.More specifically,this approach involves transferring the modified probability density functions of state prediction from the source domain to the target domain and determining the tuning factor via structure variational Bayesian inference using measurements in the target domain.Using numerical examples and a 1-DOF torsion system,we showcase the competitiveness of the proposed state estimator compared to the existing robust state estimation methods when dealing with parameter uncertainties.The results highlight its capability to improve estimation accuracy in practical scenarios,showcasing its potential for real-world applications. 展开更多
关键词 Markovian jump linear systems parameter uncertainty state estimation structure variational inference transfer learning
暂未订购 下载PDF
A Robust Hybrid WLS-EKF Algorithm for Power System State Estimation 认领 引用
3
作者 Zahid Javid Kush Lohana +1 位作者 Danial Murtaza William Holderbaum 《Energy Engineering》 EI 2026年第7期525-547,共23页
This paper introduces a novel hybrid method for Power System State Estimation(PS-SE)that effectively integrates the strengths of Weighted Least Squares(WLS)and the Extended Kalman Filter(EKF)through an adaptive weight... This paper introduces a novel hybrid method for Power System State Estimation(PS-SE)that effectively integrates the strengths of Weighted Least Squares(WLS)and the Extended Kalman Filter(EKF)through an adaptive weighting mechanism.The proposed method addresses key challenges in modern PS-SE,including measurement uncertainties,bad data detection and handling,and convergence reliability.By incorporating an adaptive weighting mechanism,the hybrid approach dynamically adjusts estimation parameters based on the quality of the measurements,enabling it to maintain high accuracy for clean data while demonstrating exceptional resilience against outliers and noisy measurements.The performance of the proposed method is rigorously evaluated against established state estimation techniques,including WLS,EKF,Bayesian method,Huber-Adaptive Method(HAM)and Neural network-based Method.Simulations are performed on IEEE 14-bus,IEEE 34-bus and IEEE 342-bus test systems to assess estimation accuracy,convergence behavior,computational efficiency,and robustness in the presence of bad data.Results highlight the superior performance of the hybrid method,which achieves higher accuracy and robust convergence properties while requiring 40%fewer iterations than conventional WLS.Despite its enhanced capabilities,the computational burden remains comparable to traditional techniques,making it highly suitable for real-time applications.These findings underscore the proposed hybrid method as a significant advancement in power system state estimation,offering a reliable,efficient,and robust solution for modern power system monitoring and control.It represents a promising approach to address the increasing complexity and data uncertainties in contemporary power grids. 展开更多
关键词 Adaptive estimation hybrid estimator power system monitoring state estimation
暂未订购 下载PDF
DGMSE:A Real-Time Dynamic Object Removal Framework Based on Detection-Guided Markov State Estimation 认领 引用
4
作者 Jiahua Kou Chengbo Guo +4 位作者 Weiyue Xing Zheng Yang Jiaxuan Cao Shufa Sun Yanling Guo 《Computers, Materials & Continua》 SCIE EI 2026年第9期1442-1472,共31页
Dynamic objects in LiDAR SLAM often introduce ghosting artifacts that degrade map quality.While offline methods can successfully clean these maps,they lack real-time capabilities.Conversely,online methods often suffer... Dynamic objects in LiDAR SLAM often introduce ghosting artifacts that degrade map quality.While offline methods can successfully clean these maps,they lack real-time capabilities.Conversely,online methods often suffer from state oscillation(where moving objects are misclassified as static when they temporarily stop)and incomplete point cloud removal.To address these challenges,we propose DGMSE,a real-time framework for removing dynamic point clouds in complex urban environments.Our approach consists of three sequential steps.First,the PointPillars 3D detection network quickly isolates potential dynamic objects,significantly reducing computational overhead.Second,to mitigate state oscillation,we introduce a five-state Markov chain to continuously estimate the probabilistic motion state of objects,which is not limited to simple moving-or-static classifications.This temporal memory prevents misclassification during sudden stops or motion transitions.Finally,instead of simply deleting all points inside a detection box,a density-adaptive clustering approach evaluates the geometric and motion characteristics of points,precisely segmenting dynamic objects from the static background without damaging permanent structures.Evaluated on the SemanticKITTI dataset,DGMSE achieves an F1-score of 0.95–0.99,achieving performance competitive with offline methods while satisfying real-time processing requirements. 展开更多
关键词 LiDAR SLAM dynamic object removal deep learning state estimation
暂未订购 下载PDF
Kalman filter based state estimation for the flexible multibody system described by ANCF 认领 引用 被引量：3
5
作者 Zuqing Yu Shuaiyi Liu Qinglong Tian 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2025年第5期207-218,共12页
The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with ... The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system. 展开更多
关键词 Nonlinear Kalman filter Absolute nodal coordinate formulation Flexible multibody system dynamics State estimation
暂未订购 下载PDF
Enhanced robustness in constant modulus blind beamforming through L1-regularized state estimation with variable-splitting Kalman smoother and IEKS 认领 引用 被引量：1
6
作者 Chuanhui HAO Bin ZHANG Xubao SUN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第6期573-590,共18页
This paper aims to enhance the array Beamforming(BF) robustness by tackling issues related to BF weight state estimation encountered in Constant Modulus Blind Beamforming(CMBB). To achieve this, we introduce a novel a... This paper aims to enhance the array Beamforming(BF) robustness by tackling issues related to BF weight state estimation encountered in Constant Modulus Blind Beamforming(CMBB). To achieve this, we introduce a novel approach that incorporates an L1-regularizer term in BF weight state estimation. We start by explaining the CMBB formation mechanism under conditions where there is a mismatch in the far-field signal model. Subsequently, we reformulate the BF weight state estimation challenge using a method known as variable-splitting, turning it into a noise minimization problem. This problem combines both linear and nonlinear quadratic terms with an L1-regularizer that promotes the sparsity. The optimization strategy is based on a variable-splitting method, implemented using the Alternating Direction Method of Multipliers(ADMM). Furthermore, a variable-splitting framework is developed to enhance BF weight state estimation, employing a Kalman Smoother(KS) optimization algorithm. The approach integrates the Rauch-TungStriebel smoother to perform posterior-smoothing state estimation by leveraging prior data. We provide proof of convergence for both linear and nonlinear CMBB state estimation technology using the variable-splitting KS and the iterated extended Kalman smoother. Simulations corroborate our theoretical analysis, showing that the proposed method achieves robust stability and effective convergence, even when faced with signal model mismatches. 展开更多
关键词 State estimation Constant modulus blind beamforming Kalman smoother Alternating direction method of multipliers Variable-splitting optimizer
暂未订购 下载PDF
DoS Attack Schedules for Remote State Estimation in CPSs With Two-hop Relay Networks Under Round-Robin Protocol 认领 引用
7
作者 Shuo Zhang Lei Miao Xudong Zhao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第7期1513-1515,共3页
Dear Editor,This letter investigates the optimal denial-of-service(DoS)attack scheduling targeting state estimation in cyber-Physical systems(CPSs)with the two-hop multi-channel network.CPSs are designed to achieve ef... Dear Editor,This letter investigates the optimal denial-of-service(DoS)attack scheduling targeting state estimation in cyber-Physical systems(CPSs)with the two-hop multi-channel network.CPSs are designed to achieve efficient,secure and adaptive operation by embedding intelligent and autonomous decision-making capabilities in the physical world.As a key component of the CPSs,the wireless network is vulnerable to various malicious attacks due to its openness[1].DoS attack is one of the most common attacks,characterized of simple execution and significant destructiveness[2].To mitigate the economic losses and environmental damage caused by DoS attacks,it is crucial to model and investigate data transmissions in CPSs. 展开更多
关键词 round robin protocol malicious attacks denial service attack two hop relay networks state estimation dos attack wireless network cyber physical systems
暂未订购 下载PDF
Collaborative State Estimation for Coupled Transmission and Distribution Systems Based on Clustering Analysis and Equivalent Measurement Modeling 认领 引用
8
作者 Hao Jiao Xinyu Liu +4 位作者 Chen Wu Chunlei Xu Zhijun Zhou Ye Chen Guoqiang Sun 《Energy Engineering》 EI 2025年第7期2977-2992,共16页
With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing hig... With the continuous expansion of the power system scale and the increasing complexity of operational mode,the interaction between transmission and distribution systems is becoming more and more significant,placing higher requirements on the accuracy and efficiency of the power system state estimation to address the challenge of balancing computational efficiency and estimation accuracy in traditional coupled transmission and distribution state estimation methods,this paper proposes a collaborative state estimation method based on distribution systems state clustering and load model parameter identification.To resolve the scalability issue of coupled transmission and distribution power systems,clustering is first carried out based on the distribution system states.As the data and models of the transmission system and distribution systems are not shared.For the transmission system,equating the power transmitted from the transmission system to the distribution system is the same as equating the distribution system.Further,the power transmitted from the transmission system to different types of distribution systems is equivalent to different polynomial equivalent load models.Then,a parameter identification method is proposed to obtain the parameters of the equivalent load model.Finally,a transmission and distribution collaborative state estimation model is constructed based on the equivalent load model.The results of the numerical analysis show that compared with the traditional master-slave splitting method,the proposed method significantly enhances computational efficiency while maintaining high estimation accuracy. 展开更多
关键词 Transmission and distribution collaboration cluster analysis parameter identification equivalent load state estimation
暂未订购 下载PDF
Optimal Sensor Scheduling for Remote State Estimation With Partial Channel Observation 认领 引用
9
作者 Bowen Sun Xianghui Cao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第7期1510-1512,共3页
Dear Editor,This letter investigates the optimal transmission scheduling problem in remote state estimation systems over an unknown wireless channel.We propose a partially observable Markov decision Process(POMDP)fram... Dear Editor,This letter investigates the optimal transmission scheduling problem in remote state estimation systems over an unknown wireless channel.We propose a partially observable Markov decision Process(POMDP)framework to model the sensor scheduling problem.By truncating and simplifying the POMDP problem,we have established the properties of the optimal solution under the POMDP model,through a fixed-point contraction method,and have shown that the threshold structure of the POMDP solution is not easily attainable.Subsequently,we obtained a suboptimal solution via Qlearning.Numerical simulations are used to demonstrate the efficacy of the proposed Q-learning approach. 展开更多
关键词 truncating simplifying remote state estimation systems optimal transmission scheduling problem threshold structure sensor scheduling optimal solution partially observable markov decision process partially observable markov decision process pomdp framework
暂未订购 下载PDF
Improved Zero-Dynamics Attack Scheduling With State Estimation 认领 引用 被引量：2
10
作者 Zhe Wang Heng Zhang +1 位作者 Chaoqun Yang Xianghui Cao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第2期472-474,共3页
Dear Editor,This letter focuses on how an attacker can design suitable improved zero-dynamics (ZD) attack signal based on state estimates of target system. Improved ZD attack is to change zero dynamic gain matrix of a... Dear Editor,This letter focuses on how an attacker can design suitable improved zero-dynamics (ZD) attack signal based on state estimates of target system. Improved ZD attack is to change zero dynamic gain matrix of attack signal to a matrix with determinant greater than 1. 展开更多
关键词 change zero dynamic gain matrix target system state estimation scheduling attack signal improved zd state estimates improved zero dynamics attack
暂未订购 下载PDF
Factor graph method for target state estimation in bearing-only sensor network 认领 引用
11
作者 CHEN Zhan FANG Yangwang +1 位作者 ZHANG Ruitao FU Wenxing 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第2期380-396,共17页
For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation.... For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation.This paper pro-poses a distributed state estimation method based on two-layer factor graph.Firstly,the measurement model of the bearing-only sensor network is constructed,and by investigating the observ-ability and the Cramer-Rao lower bound of the system model,the preconditions are analyzed.Subsequently,the location fac-tor graph and cubature information filtering algorithm of sensor node pairs are proposed for localized estimation.Building upon this foundation,the mechanism for propagating confidence mes-sages within the fusion factor graph is designed,and is extended to the entire sensor network to achieve global state estimation.Finally,groups of simulation experiments are con-ducted to compare and analyze the results,which verifies the rationality,effectiveness,and superiority of the proposed method. 展开更多
关键词 factor graph cubature information filtering bearing-only sensor network state estimation
暂未订购 下载PDF
Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity 认领 引用 被引量：9
12
作者 Lei Zou Zidong Wang +2 位作者 Bo Shen Hongli Dong Guoping Lu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2023年第4期985-996,共12页
This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying systems.Due to the inherent vulnerability of network-based communication,the measu... This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying systems.Due to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential eavesdroppers.To avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption scheme.The purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l2-l∞performance is achieved.Sufficient conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state estimator.Finally,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme. 展开更多
关键词 Artificial-noise-assisted technique eavesdropping encryption-decryption scheme energy-to-peak state estimation finitehorizon state estimation
暂未订购 下载PDF
Power System State Estimation Solution With Zero Injection Constraints Using Modified Newton Method and Fast Decoupled Method in Polar Coordinate 认领 引用 被引量：14
13
作者 GUO Ye ZHANG Boming +1 位作者 WU Wenchuag SUN Hongbin 《中国电机工程学报》 EI CSCD 北大核心 2012年第22期I0015-I0015,11,共1页
In actual power systems,most of the high-voltage buses of the transformers are zero injection buses without load or generation.Power injections into these buses are strictly 0,so based on Kirchhoff's current law(K... In actual power systems,most of the high-voltage buses of the transformers are zero injection buses without load or generation.Power injections into these buses are strictly 0,so based on Kirchhoff's current law(KCL),equality constraints should be used to handle these buses in a state estimation model.It is a challenge to ensure that these zero injection constraints can be strictly satisfied without losing computational efficiency. 展开更多
关键词 state estimation zero injection equality constraints polar coordinate modified Newton method modified fast decoupled state estimation
暂未订购 下载PDF
A Sensorless State Estimation for A Safety-Oriented Cyber-Physical System in Urban Driving:Deep Learning Approach 认领 引用 被引量：8
14
作者 Mohammad Al-Sharman David Murdoch +4 位作者 Dongpu Cao Chen Lv Yahya Zweiri Derek Rayside William Melek 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2021年第1期169-178,共10页
In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the vehicle.As a typical CPS,the braking system is crucia... In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the vehicle.As a typical CPS,the braking system is crucial for the vehicle design and safe control.However,precise state estimation of the brake pressure is desired to perform safe driving with a high degree of autonomy.In this paper,a sensorless state estimation technique of the vehicle's brake pressure is developed using a deep-learning approach.A deep neural network(DNN)is structured and trained using deep-learning training techniques,such as,dropout and rectified units.These techniques are utilized to obtain more accurate model for brake pressure state estimation applications.The proposed model is trained using real experimental training data which were collected via conducting real vehicle testing.The vehicle was attached to a chassis dynamometer while the brake pressure data were collected under random driving cycles.Based on these experimental data,the DNN is trained and the performance of the proposed state estimation approach is validated accordingly.The results demonstrate high-accuracy brake pressure state estimation with RMSE of 0.048 MPa. 展开更多
关键词 Brake pressure state estimation cyber-physical system(CPS) deep learning dropout regularization approach
暂未订购 下载PDF
Coupled dynamic model of state estimation for hypersonic glide vehicle 认领 引用 被引量：14
15
作者 ZHANG Kai XIONG Jiajun FU Tingting 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第6期1284-1292,共9页
Aiming at handling complicated maneuvers or other unpredicted emergencies for hypersonic glide vehicle tracking,three coupled dynamic models of state estimation based on the priori information between guidance variabl... Aiming at handling complicated maneuvers or other unpredicted emergencies for hypersonic glide vehicle tracking,three coupled dynamic models of state estimation based on the priori information between guidance variables and aerodynamics are presented. Firstly, the aerodynamic acceleration acting on the target is analyzed to reveal the essence of the target’s motion.Then three coupled structures for modeling aerodynamic parameters are developed by different ideas: the spiral model with a harmonic oscillator, the bank model with trigonometric functions of the bank angle and the guide model with the changing rule of guidance variables. Meanwhile, the comparison discussion is concluded to show the novelty and advantage of these models.Finally, a performance assessment in different simulation cases is presented and detailed analysis is revealed. The results show that the proposed models perform excellent properties. Moreover, the guide model produces the best tracking performance and the bank model shows the second; however, the spiral model does not outperform the maneuvering reentry vehicle(MaRV) model markedly. 展开更多
关键词 hypersonic glide vehicle state estimation dynamic model aerodynamic parameter guidance variable
暂未订购 下载PDF
Adaptive unscented Kalman filter for parameter and state estimation of nonlinear high-speed objects 认领 引用 被引量：12
16
作者 Fang Deng Jie Chen Chen Chen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第4期655-665,共11页
An adaptive unscented Kalman filter(AUKF)and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects.A strong tracking filter is employed to i... An adaptive unscented Kalman filter(AUKF)and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects.A strong tracking filter is employed to improve the tracking ability and robustness of unscented Kalman filter(UKF)when the process noise is inaccuracy,and wavelet transform is used to improve the estimate accuracy by the variance of measurement noise.An augmented square-root framework is utilized to improve the numerical stability and accuracy of UKF.Monte Carlo simulations and applications in the rapid trajectory estimation of hypersonic artillery shells confirm the effectiveness of the proposed method. 展开更多
关键词 parameter estimation state estimation unscented Kalman filter(UKF) strong tracking filter wavelet transform.
暂未订购 下载PDF
State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters 认领 引用 被引量：4
17
作者 S.Lakshmanan Ju H.Park +1 位作者 H.Y.Jung P.Balasubramaniam 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第10期29-37,共9页
This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed timevarying delays and Markovian jumping parameters.The addressed neural networks have a finite number of mode... This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed timevarying delays and Markovian jumping parameters.The addressed neural networks have a finite number of modes,and the modes may jump from one to another according to a Markov process.By construction of a suitable Lyapunov-Krasovskii functional,a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square.The criterion is formulated in terms of a set of linear matrix inequalities（LMIs）,which can be checked efficiently by use of some standard numerical packages. 展开更多
关键词 neural networks state estimation neutral delay Markovian jumping parameters
暂未订购 下载PDF
Reconstruction of measurements in state estimation strategy against deception attacks for cyber physical systems 认领 引用 被引量：3
18
作者 Qinxue LI Bugong XU +2 位作者 Shanbin LI Yonggui LIU Delong CUI 《Control Theory and Technology》 EI CSCD 2018年第1期1-13,共13页
Without the known state equation, a new state estimation strategy is designed to be against malicious attacks for cyber physical systems. Inspired by the idea of data reconstruction, the compressive sensing （CS） is ... Without the known state equation, a new state estimation strategy is designed to be against malicious attacks for cyber physical systems. Inspired by the idea of data reconstruction, the compressive sensing （CS） is applied to reconstruction of residual measurements after the detection and identification scheme based on the Markov graph of the system state, which increases the resilience of state estimation strategy against deception attacks. First, the observability analysis is introduced to decide the triggering time of the measurement reconstruction and the damage level from attacks. In particular, the dictionary learning is proposed to form the over-completed dictionary by K-singular value decomposition （K-SVD）, which is produced adaptively according to the characteristics of the measurement data. In addition, due to the irregularity of residual measurements, a sampling matrix is designed as the measurement matrix. Finally, the simulation experiments are performed on 6-bus power system. Results show that the reconstruction of measurements is completed well by the proposed reconstruction method, and the corresponding effects are better than reconstruction scheme based on the joint dictionary and the traditional Gauss or Bernoulli random matrix respectively. Especially, when only 29% available clean measurements are left, performance of the proposed strategy is still extraordinary, which reflects generality for five kinds of recovery algorithms. 展开更多
关键词 State estimation deception attacks cyber physical systems reconstruction of measurements compressivesensing
Distributed state estimation for heterogeneous mobile sensor networks with stochastic observation loss 认领 引用 被引量：3
19
作者 Yingrong YU Jianglong YU +1 位作者 Yishi LIU Zhang REN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2022年第2期265-275,共11页
The problem of distributed fusion and random observation loss for mobile sensor networks is investigated herein.In view of the fact that the measured values,sampling frequency and noise of various sensors are differen... The problem of distributed fusion and random observation loss for mobile sensor networks is investigated herein.In view of the fact that the measured values,sampling frequency and noise of various sensors are different,the observation model of a heterogeneous network is constructed.A binary random variable is introduced to describe the drop of observation component and the topology switching problem caused by complete observation loss is also considered.A cubature information filtering algorithm is adopted to design local filters for each observer to suppress the negative effects of measurement noise.To derive a consistent and accurate estimation result,a novel weighted average consensus-based filtering approach is put forward.For the sensor that suffers from observation loss,its local prediction information vector is fused with the information contribution vectors of the neighbors to obtain the local estimation.Then the consensus weight matrix is designed for consensus-based distributed collaborative information fusion.The boundness of the estimation errors is proved by employing the stochastic stability theory.In the end,two numerical examples are offered to assert the validity of the presented method. 展开更多
关键词 Consistency theorem Heterogeneous sensor networks Information fusion State estimation Stochastic boundedness
暂未订购 下载PDF
Modeling and Analysis of Soft Bionic Fingers for Contact State Estimation 认领 引用 被引量：3
20
作者 Yongyao Li Ming Cong +1 位作者 Dong Liu Yu Du 《Journal of Bionic Engineering》 SCIE EI CSCD 2022年第6期1699-1711,共13页
Contact state estimation is significant for evaluating grasp stability of bionic hands,especially in unknown environments or without visualactile feedback.It still remains challenging,particularly for soft bionic hand... Contact state estimation is significant for evaluating grasp stability of bionic hands,especially in unknown environments or without visualactile feedback.It still remains challenging,particularly for soft bionic hands without integrating complicated external sensors on soft fingers.Focusing on this issue,a proprioceptive-sensing-based systematic solution is proposed to estimate the contact state of soft bionic fingers in a single grasp.A kinematic model for soft fingers is first developed to capture the joint rotation angles and tendon displacement.A kinetostatic model is further built to estimate the contact force when soft fingers come in contact with objects.On this basis,a system stiffness model for soft fingers during preshaping and initial contact with objects is proposed to perceive the contact state.Moreover,an instantaneous stiffness model for soft fingers when initial contact occurs is developed for estimating the contact position on certain phalanges,especially the contact position along the distal phalange.The proposed proprioceptive-sensing-based approach is the first application in soft fingers without integrating complicated external sensors,which makes them concise and practical.Experiments are carried out to demonstrate the effectiveness and efficiency of our proposal. 展开更多
关键词 Proprioceptive-sensing-based modeling Soft bionic hand Contact state estimation Stiffness analysis
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 16 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈