Article
Engineering, Electrical & Electronic
Kejia Zhu, Youqing Wang
Summary: This paper studies the problem of sensor fault estimation in Unmanned Surface Vehicle systems in a networked environment. An observer based on an event-trigger mechanism is proposed to estimate the state and sensor fault, with the trigger threshold adjusted to balance observer performance and energy consumption. Simulation experiments validate the effectiveness of the observer design and the boundedness of estimation error.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Xiao-Lei Wang, Guang-Hong Yang, Dianhua Zhang
Summary: This article addresses the problem of event-triggered fault detection observer design for Takagi-Sugeno fuzzy systems, proposing switched fuzzy FD observers based on online asynchronous premise reconstruction. The use of new Lyapunov functions shows that the proposed FD observers can ensure system stability and desired performance.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Bin Li, Xinglian Zhou, Zhaoke Ning, Xiaoyi Guan, Ka-Fai Cedric Yiu
Summary: This article investigates a dynamic event-triggered security control problem in networked control systems under deception attacks and packet dropouts. A combined cyberattack model is proposed to reflect randomly occurring cyber-attacks. A dynamic event-triggered protocol is constructed to reduce data transmission and relieve bandwidth pressure. An online model predictive control algorithm is established to ensure stochastic stability and expected performance. Two examples are simulated to verify the effectiveness of the proposed design strategy.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Xudong Wang, Zhongyang Fei, Jianbin Qiu, Huijun Gao
Summary: This article discusses zonotopic fault detection for fuzzy systems with event-triggered mechanism, proposing an l(1)/h(infinity) fault detector design method and constructing a zonotopic residual evaluation process. Different from most existing works, zonotopic thresholds for residual signal are designed by considering the influences of disturbance, noise, asynchronous premise variables, and event-based transmission. The effective performance of the developed strategy is verified through a numerical example.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Zhou Gu, Dong Yue, Ju H. Park, Xiangpeng Xie
Summary: This article investigates the networked fault detection problem for interval type-2 T-S fuzzy systems and proposes a novel adaptive memory-event-triggered mechanism (METM) to reduce the data releasing rate and avoid maltriggering events.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Yuan Liu, Qiang Ling
Summary: This article studies the quantized control problem of a scalar continuous-time linear system over a digital network. By analyzing the evolution of the uncertainty set of the system state, a lower bound on the necessary bit rate for any event-triggered strategy is derived, and a control strategy combining event-triggering and time-triggering is proposed to stabilize the system. Numerical examples are provided to illustrate the obtained results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Mali Xing, Feiqi Deng, Panshuo Li, Hao Yin, Muqing Deng
Summary: This paper discusses the mean-square leader-following consensus problem for heterogeneous multi-agent systems affected by noises. A distributed dynamic control method and event-triggered mechanism are proposed, with the utilization of time-delay model method and time-varying Hanaly inequality to ensure system consensus, along with a quantity-based event-triggered mechanism to reduce traffic volume.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Mathematics, Applied
Chengchao Li, Chunyu Wu, E. Abozinadah, Madini O. Alassafi, Ning Xu
Summary: This paper investigates the output-based event-triggered control problem of discrete-time networked control systems subject to bilateral packet dropouts. The NCS is converted into a closed-loop stochastic parameter system considering the stochastic sequences of packet dropouts. Sufficient conditions are derived using a Lyapunov functional based on stochastic variables to guarantee the exponentially mean-square stability. An improved iterative algorithm is proposed to obtain the output-based control law and event-triggering parameters.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Lin-Xing Xu, Yu-Long Wang, Xiaofan Wang, Chen Peng
Summary: This article considers the problem of decentralized event-triggered fault-tolerant control for interconnected nonlinear systems with unknown strong coupling and actuator failures. A new decentralized adaptive control scheme is proposed to enable each subsystem output to track the desired trajectory. The effectiveness of the proposed scheme is demonstrated by a practical interconnected system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Qian Zhang, Huaicheng Yan, Meng Wang, Zhichen Li, Yufang Chang
Summary: This article addresses the problem of asynchronous fault detection filter (FDF) design for Takagi-Sugeno (T-S) fuzzy singular systems using a dynamic event-triggered scheme. The mode-dependent dynamic event-triggered scheme is adopted to reduce the communication load. A hidden Markov model is introduced to capture the asynchronous phenomenon between the system and the FDF. Sufficient criteria are established to ensure the stochastically admissible residual system with a certain H-8 performance. Solvability criteria are presented to co-design the desired FDF gains and event-triggered matrices. The proposed method is validated through two examples.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Theory & Methods
Yajuan Liu, Xueyun Zhao, Ju H. Park, Fang Fang
Summary: This article investigates the problem of exponential stabilization for Takagi-Sugeno (T-S) fuzzy systems with actuator faults and aperiodic sampling. It first designs a fault-tolerant control strategy for T-S fuzzy systems under a given actuator fault model. Then, an improved aperiodic adaptive event-triggered (AET) control scheme is established, which updates the threshold adaptively during the sampling process to greatly reduce the amount of transmitted information. Two sufficient exponential stability conditions are derived based on the Lyapunov-Krasovskii functional (LKF) method. Additionally, a corresponding sampled-data controller is designed according to the stability conditions and fault-tolerant mechanism. Finally, the virtue and effectiveness of the proposed scheme are demonstrated through a numerical example and a simplified gas turbine system.
FUZZY SETS AND SYSTEMS
(2023)
Article
Automation & Control Systems
Bing Chen, Yangzhou Chen, Jingyuan Zhan
Summary: This paper addresses the periodic event-triggered consensus problem for linear multiagent systems with random packet dropouts in a generic directed communication topology. Both leaderless and leader-following mean square consensus problems are considered, and a linear transformation matrix is constructed to transform the mean square consensus problem into the corresponding mean square asymptotic stability problem. Mean square consensus criteria are derived using Lyapunov stability theory in terms of linear matrix inequalities concerning the sampling period, the packet dropout probability, and the control gain matrix. An event-triggered mechanism is designed to reduce the information updating number.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Computer Science, Information Systems
Xiao-Lei Wang, Li-Ying Hao
Summary: This paper investigates the design of event-triggered fault detection observers for T-S fuzzy systems. An improved matching membership function method is proposed to provide design flexibility. By establishing equality constraints, the membership functions of the residual generator can be obtained directly without calculation. New criteria based on linear matrix inequalities are derived to ensure the desired performance of the FD system. The proposed method overcomes the shortcomings of existing results and is verified through an example.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Zhongyao Hu, Bo Chen, Wen-An Zhang, Li Yu
Summary: This paper focuses on solving the event-triggered multi-sensor fusion estimation problem with bounded noises. In the centralized fusion framework, a compensation strategy is developed to recover the non-triggered data, and an optimal estimator is derived by minimizing the estimation error. In the distributed fusion framework, optimal local estimators are obtained on each observable subspace, and two different distributed fusion estimators are designed using spectral radius inequality and trace inequality, respectively.
Article
Computer Science, Artificial Intelligence
Yao Wen, Xin Ye, Xiaojie Su
Summary: This article focuses on the fault detection filtering problem for a nonlinear dynamic system in the Takagi-Sugeno fuzzy framework. An event-triggered scheme is used considering network bandwidth utilization rate and fault occurrence probability, which can save communication resources and reduce computational burden. The proposed event-based fault detection scheme is robust against exogenous disturbances and sensitive to system faults, and it has asymptotic stability with a specified H-infinity error property.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Alam Abbas Syed, Hassan Foroosh
Summary: This paper presents effective methods using spherical polar Fourier transform data for two different applications: 3D volumetric registration and machine learning classification network. The proposed method for registration offers unique and effective techniques, handling arbitrary large rotation angles and showing robustness. The modified classification network achieves robust classification results in processing spherical data.
Article
Engineering, Electrical & Electronic
Ruibo Fan, Mingli Jing, Jingang Shi, Lan Li, Zizhao Wang
Summary: In this study, a new low-rank sparse decomposition algorithm named TVRPCA+ is proposed for foreground-background separation. The algorithm combines spectral norm, structured sparse norm, and total variation regularization to suppress noise and obtain cleaner foregrounds. Experimental results demonstrate that TVRPCA+ achieves high performance in complex backgrounds and noise scenarios.
Article
Engineering, Electrical & Electronic
Omair Aldimashki, Ahmet Serbes
Summary: This paper proposes a coarse-to-fine FrFT-based algorithm for chirp-rate estimation of multi-component LFM signals, which achieves improved performance and a reduced signal-to-noise breakdown threshold by utilizing mathematical models for coarse estimation and a refined estimate-and-subtract strategy. Extensive simulation results demonstrate that the proposed algorithm performs very close to the Cramer-Rao lower bound, with the advantages of eliminating leakage effect, avoiding error propagation, and maintaining acceptable computational cost compared to other state-of-the-art methods.
Article
Engineering, Electrical & Electronic
Xinlei Shi, Xiaofei Zhang, Yuxin Sun, Yang Qian, Jinke Cao
Summary: In this paper, a low-complexity localization approach for multiple sources using two-dimensional discrete Fourier transform (2D-DFT) is proposed. The method computes the cross-covariance and utilizes phase offset method and total least square solution to obtain accurate position estimates.
Article
Engineering, Electrical & Electronic
Prabhanjan Mannari, Ratnasingham Tharmarasa, Thiagalingam Kirubarajan
Summary: This paper discusses the problem of extended target tracking for a single 2D extended target with a known convex polytope shape and dynamics. It proposes a framework based on the existing point multitarget tracking framework to address the challenges of uncertainty in shape and kinematics, as well as self-occlusion. The algorithm developed using this framework is capable of dynamically changing the number of parameters used to describe the shape and estimating the whole target shape even when different parts of the target are visible at different frames.
Article
Engineering, Electrical & Electronic
Yongsong Li, Zhengzhou Li, Jie Li, Junchao Yang, Abubakar Siddique
Summary: This paper proposes a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The WARTH method effectively measures local and global feature information using an adaptive ring-shaped structural element and a target awareness indicator, resulting in accurate detection of small targets with minimized false alarms.
Article
Engineering, Electrical & Electronic
Yu Wang, Zhen Qin, Jun Tao, Yili Xia
Summary: In this paper, an enhanced sparsity-aware recursive least squares (RLS) algorithm is proposed, which combines the proportionate updating (PU) and zero-attracting (ZA) mechanisms, and introduces a general convex regularization (CR) function and variable step-size (VSS) technique to improve performance.
Article
Engineering, Electrical & Electronic
Neil J. Bershad, Jose C. M. Bermudez
Summary: This paper analyzes the impact of processing delay on the Least Mean Squares (LMS) algorithm in system identification, highlighting bias issues in the resulting weight vector.
Article
Engineering, Electrical & Electronic
Kanghui Jiang, Defu Jiang, Mingxing Fu, Yan Han, Song Wang, Chao Zhang, Jingyu Shi
Summary: In this paper, a novel method for velocity estimation using multicarrier signals in a single dwell is proposed, which effectively addresses the issue of Doppler ambiguity in pulse Doppler radars.
Article
Engineering, Electrical & Electronic
Xiao-Jun Zhang, Peng-Lang Shui, Yu-Fan Xue
Summary: This paper proposes a method for low-velocity small target detection in maritime surveillance radars. It models sea clutter sequences using the spherical invariant random vector (SIRV) model with block tridiagonal speckle covariance matrix and inverse Gamma distributed texture. The proposed detector, which is a long-time adaptive generalized likelihood ratio test with linear threshold detector (GLRT-LTD), shows competitive detection performance in experiments.
Article
Engineering, Electrical & Electronic
Aiyi Zhang, Fulai Liu, Ruiyan Du
Summary: This paper proposes an adaptive weighted robust data recovery method with total variation regularization for hyperspectral image. The method models the HSI recovery problem as a tensor robust principal component analysis optimization problem, decomposing the data into low-rank HSI data, outliers, and noise component. An adaptive weighted strategy is then defined to impose on the tensor nuclear norm and outliers, using the priori information of singular values and strengthening the sparsity of outliers.
Article
Engineering, Electrical & Electronic
Hamid Asadi, Babak Seyfe
Summary: This paper presents a novel approach for estimating the model order in the presence of observation errors. The proposed method is based on correntropy estimation of eigenvalues in the observation space, which is further enhanced by resampling the observations using the bootstrap method. The algorithm partitions the observation space into signal and noise subspaces using the covariance matrix of mixtures, and determines the model order based on a correntropy estimator with kernel functions. Theoretical analysis and comparative evaluations demonstrate the superiority of this information-theoretic approach.
Article
Engineering, Electrical & Electronic
Buket colak Guvenc, Engin Cemal Menguc
Summary: In this paper, a novel family of online censoring based complex-valued least mean kurtosis (CLMK) algorithms is proposed. The algorithms censor less informative complex-valued data streams and reduce the costs of data processing without affecting accuracy. Robust algorithms are also developed to handle outliers. The simulation results confirm the attractive features of the proposed algorithms in large-scale system identification and regression scenarios.
Article
Engineering, Electrical & Electronic
Yun Su, Weixian Tan, Yifan Dong, Wei Xu, Pingping Huang, Jianxin Zhang, Diankun Zhang
Summary: In this study, a novel method for detecting low-resolution and small targets in millimeter wave radar images is proposed. The Wavelet-Conv structure and Wavelet-Attention mechanism are introduced to overcome the limitations of existing detectors. Experimental results demonstrate that the proposed method improves recall and mean average precision while maintaining competitive inference speed.
Article
Engineering, Electrical & Electronic
Xin Wang, Xingxing Jiang, Qiuyu Song, Jie Liu, Jianfeng Guo, Zhongkui Zhu
Summary: This study proposes a variational mode extraction (VME) method for extracting specific modes from complicated signals. By exploring the convergence property of VME, strategies for identifying ICF and determining the balance parameter are designed, and a bandwidth estimation strategy is constructed. The effectiveness of the proposed method for bearings fault diagnosis is verified and compared with other methods.