IEEE Transactions on Systems, Man, and Cybernetics: Systems
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Year: 2022 | Volume: 52 | Issue: 2
IEEE Transactions on Systems, Man, and Cybernetics publication information
Publication Year: 2022,Page(s):C2 - C2
IEEE Transactions on Systems, Man, and Cybernetics publication information
Year: 2022 | Volume: 52 | Issue: 2
Global Stabilization for a Class of Switched Nonlinear Time-Delay Systems via Sampled-Data Output-Feedback Control
Publication Year: 2022,Page(s):694 - 705
Cited by: Papers (35)
This article presents a stabilization achievement for a switched nonlinear time-delay system through output-feedback control under the sampled-data and global senses. An observer with the sampled output measurement is constructed to evaluate the unavailable states, and then a controller formed from the sampled observer states is given. For the stability analysis, a merging virtual switching signal...Show More
Robust ℓ₁-Controller Design for Discrete-Time Positive T–S Fuzzy Systems Using Dual Approach
Publication Year: 2022,Page(s):706 - 715
Cited by: Papers (22)
In this article, a new approach is proposed for stability analysis and controller design of nonlinear discrete-time positive systems by means of the Takagi–Sugeno fuzzy model. The closed-loop stability and the positivity constraint are guaranteed by synthesizing a linear co-positive Lyapunov function and by applying the parallel distributed compensation controller. In contrast to the state-...Show More
Smart Train Operation Algorithms Based on Expert Knowledge and Reinforcement Learning
Publication Year: 2022,Page(s):716 - 727
Cited by: Papers (29)
During decades, the automatic train operation (ATO) system has been gradually adopted in many subway systems for its low-cost and intelligence. This article proposes two smart train operation (STO) algorithms by integrating the expert knowledge with reinforcement learning algorithms. Compared with previous works, the proposed algorithms can realize the control of continuous action for the subway s...Show More
Learn How to Assist Humans Through Human Teaching and Robot Learning in Human–Robot Collaborative Assembly
Publication Year: 2022,Page(s):728 - 738
Cited by: Papers (20)
Human–robot collaborative assembly has been one of the next-generation manufacturing paradigms in which superiorities of humans and robots can be fully leveraged. To enable robots effectively collaborate with humans, similar to human–human collaboration, robot learning from human demonstrations has been adopted to learn the assembly tasks. However, existing feature-based approaches r...Show More
Control System Design of a Three-Phase Active Front End Using a Sliding-Mode Observer
Wensheng Luo;Sergio Vazquez;Jianxing Liu;Francisco Gordillo;Leopoldo G. Franquelo;Ligang Wu
Publication Year: 2022,Page(s):739 - 748
Cited by: Papers (22)
This article proposes a sliding-mode-observer (SMO)-based control strategy to regulate the dc-link voltage for a three-phase two-level active front end (AFE). The SMO is designed for the voltage control loop to estimate the external load which is abruptly connected to the AFE dc-link and consequently causes the dc-link voltage fluctuation. The estimated load value is used to compensate the voltage...Show More
On Training Traffic Predictors via Broad Learning Structures: A Benchmark Study
Publication Year: 2022,Page(s):749 - 758
Cited by: Papers (29)
A fast architecture for real-time (i.e., minute-based) training of a traffic predictor is studied, based on the so-called broad learning system (BLS) paradigm. The study uses various traffic datasets by the California Department of Transportation, and employs a variety of standard algorithms (LASSO regression, shallow and deep neural networks, stacked autoencoders, convolutional, and recurrent neu...Show More
Robust Fixed-Time Stabilization Control of Generic Linear Systems With Mismatched Disturbances
Publication Year: 2022,Page(s):759 - 768
Cited by: Papers (68)
This article addresses the robust fixed-time stabilization control problem for generic linear systems with both matched and mismatched disturbances. A new observer-based fixed-time control technique is proposed to solve this robust stabilization problem, provided that the system matrix pair $(A,B)$ is controllable. The ultimate boundedness of the closed-loop system in the presence of mismatched ...Show More
ε-Constrained Differential Evolution Using an Adaptive ε-Level Control Method
Chunjiang Zhang;A. K. Qin;Weiming Shen;Liang Gao;Kay Chen Tan;Xinyu Li
Publication Year: 2022,Page(s):769 - 785
Cited by: Papers (22)
Evolutionary algorithms and swarm intelligence algorithms have been widely used for constrained optimization problems for decades and numerous techniques for constraint handling have been proposed. The ${\varepsilon }$ -constrained method is a very effective one. In the literature, the ${\varepsilon }$ value was usually controlled via an exponential function, which is not competent for solving ...Show More
Adaptive Offspring Generation for Evolutionary Large-Scale Multiobjective Optimization
Publication Year: 2022,Page(s):786 - 798
Cited by: Papers (132)
Offspring generation plays an important role in evolutionary multiobjective optimization. However, generating promising candidate solutions effectively in high-dimensional spaces is particularly challenging. To address this issue, we propose an adaptive offspring generation method for large-scale multiobjective optimization. First, a preselection strategy is proposed to select a balanced parent po...Show More
Composite Adaptive Disturbance Observer-Based Decentralized Fractional-Order Fault-Tolerant Control of Networked UAVs
Ziquan Yu;Youmin Zhang;Bin Jiang;Jun Fu;Ying Jin;Tianyou Chai
Publication Year: 2022,Page(s):799 - 813
Cited by: Papers (60)
This article considers the decentralized fractional-order fault-tolerant control problem for unmanned aerial vehicles (UAVs) against wind disturbances and actuator faults in a directed communication network. A new composite adaptive disturbance observer-based decentralized fractional-order fault-tolerant control (CADOB-DFO-FTC) scheme, which incorporates fractional-order (FO) sliding-mode surfaces...Show More
Membership Function-Dependent Local Controller Design for T–S Fuzzy Systems
Publication Year: 2022,Page(s):814 - 821
Cited by: Papers (21)
For the conservatism issue of state-feedback control for Takagi–Sugeno (T–S) fuzzy systems, a novel local controller design method and stability analysis approach are proposed in this article. First, based on a membership function piecewise linearization technique, a local linear controller is proposed to form a closed-loop system. Then, a series of system stability conditions are derived using qu...Show More
Stochastic Stability Analysis and Synthesis of a Class of Human-in-the-Loop Control Systems
Publication Year: 2022,Page(s):822 - 832
Cited by: Papers (13)
There have been a wide variety of practical control applications having human in the loop in today’s society, such as automobile systems, health care, and energy management. In this article, a Markov jump system with controlled and hidden modes (MJSCHM) is employed to model a class of human-in-the-loop (HiTL) control systems which passively monitor human internal state (HIS) and take appropriate c...Show More
Development and Motion Control of Biomimetic Underwater Robots: A Survey
Publication Year: 2022,Page(s):833 - 844
Cited by: Papers (68)
Biomimetic underwater robots have attracted considerable research attention globally, owing to their quieter actuations, higher propulsion efficiency, and stronger maneuverability when compared with conventional underwater vehicles equipped with axial propellers. This article provides a comprehensive survey of current research in this field. First, we review the development status of biomimetic un...Show More
Initialization-Free Distributed Fixed-Time Convergent Algorithms for Optimal Resource Allocation
Publication Year: 2022,Page(s):845 - 854
Cited by: Papers (34)
This article considers the distributed fixed-time resource allocation problem subject to global equality and local inequality constraints. In the case that the optimal solutions are strictly feasible, a projection-gradient-based continuous-time algorithm is first proposed to minimize a team of cost functions in the fixed time. As some optimal solutions locate on the boundary of local constraints, ...Show More
Toward Packet Routing With Fully Distributed Multiagent Deep Reinforcement Learning
Xinyu You;Xuanjie Li;Yuedong Xu;Hui Feng;Jin Zhao;Huaicheng Yan
Publication Year: 2022,Page(s):855 - 868
Cited by: Papers (51)
Packet routing is one of the fundamental problems in computer networks in which a router determines the next-hop of each packet in the queue to get it as quickly as possible to its destination. Reinforcement learning (RL) has been introduced to design autonomous packet routing policies with local information of stochastic packet arrival and service. However, the curse of dimensionality of RL prohi...Show More
An Improved Sparse Autoencoder and Multilevel Denoising Strategy for Diagnosing Early Multiple Intermittent Faults
Publication Year: 2022,Page(s):869 - 880
Cited by: Papers (25)
Currently, the diagnosis of single fault marked by distinct characteristics has received mass concern, and the related research achievements are remarkable. However, the diagnosis of early multiple intermittent (EMI) faults commonly existing in industrial systems is still an intractable problem, owing to: 1) the scarcity of fault data and the faintness of features and 2) the mutual interaction of ...Show More
Enhanced Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems Based on a Comprehensive Real-Time Scheduling Model
Publication Year: 2022,Page(s):881 - 892
Cited by: Papers (25)
The problem of enhanced stabilization of discrete-time Takagi–Sugeno fuzzy system is investigated in depth via proposing a new way to employ much more information implied in various time-varying differences of multi-instant normalized fuzzy weighting functions. Benefit from the given comprehensive real-time scheduling model, these time-varying differences on time vertical dimension and two differe...Show More
Disturbance Observer-Based Active Vibration Suppression and Attitude Control for Flexible Spacecraft
Publication Year: 2022,Page(s):893 - 901
Cited by: Papers (33)
In this article, active vibration suppression and attitude control for flexible spacecraft under model uncertainty and external disturbance are investigated. First, an adaptive disturbance observer (ADO) and flexible vibration observer (FVO) are proposed to estimate the lumped uncertainty and flexible vibration. It is shown that the proposed ADO is nonoverestimated and the first derivative upper b...Show More
Stochastic Game in Linear Quadratic Gaussian Control for Wireless Networked Control Systems Under DoS Attacks
Publication Year: 2022,Page(s):902 - 910
Cited by: Papers (19)
Recently, the security problem of wireless networked control systems (WNCSs) has become critical. In this article, we focus on strategies designing problem for sensor and denial-of-service (DoS) attacker in WNCS based on linear quadratic Gaussian (LQG) cost. In this scenario, a sensor measures the output of the system and transmits its local state estimate to the remote estimator via an unreliable...Show More
Stochastic and Deterministic State-Dependent Social Networks
Daniel Silvestre;Paulo Rosa;João P. Hespanha;Carlos Silvestre
Publication Year: 2022,Page(s):911 - 926
Cited by: Papers (6)
This article investigates a political party or an association social network where members share a common set of beliefs. In modeling it as a distributed iterative algorithm with network dynamics mimicking the interactions between people, the problem of interest becomes that of determining: 1) the conditions when convergence happens in finite time and 2) the corresponding steady-state opinion. For...Show More
Security Analysis of Discrete Nonlinear Systems With Injection Attacks Under Iterative Learning Schemes
Publication Year: 2022,Page(s):927 - 935
Cited by: Papers (8)
In this study, the security problem of discrete nonlinear systems with injection attacks is discussed by designing two kinds of iterative learning schemes with the partial information and delay. The definitions of security and insecurity are presented and the injection attack is considered in a discrete nonlinear system. The contribution of this study is twofold: 1) two kinds of iterative learning...Show More
A Survey of the Four Pillars for Small Object Detection: Multiscale Representation, Contextual Information, Super-Resolution, and Region Proposal
Guang Chen;Haitao Wang;Kai Chen;Zhijun Li;Zida Song;Yinlong Liu;Wenkai Chen;Alois Knoll
Publication Year: 2022,Page(s):936 - 953
Cited by: Papers (160)
Although great progress has been made in generic object detection by advanced deep learning techniques, detecting small objects from images is still a difficult and challenging problem in the field of computer vision due to the limited size, less appearance, and geometry cues, and the lack of large-scale datasets of small targets. Improving the performance of small object detection has a wider sig...Show More
Distributed Adaptive Fuzzy Fault-Tolerant Containment Control for Heterogeneous Nonlinear Multiagent Systems
Publication Year: 2022,Page(s):954 - 965
Cited by: Papers (60)
This article is concerned with the problem of distributed adaptive fuzzy fault-tolerant containment control (FTCC) for a class of heterogeneous nonlinear multiagent systems with actuator faults and external disturbances. Two FTCC strategies are proposed for two different cases, i.e., leader’s input can be obtained by its neighboring follower agents and the input of the leader is not available by a...Show More
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Editor-in-Chief
Professor
University of Massachusetts Amherst, College of Information and Computer Sciences; University of Memphis
Amherst
USA
trans.smcsystems.eic@gmail.comContact Information
Editor-in-Chief
Professor
University of Massachusetts Amherst, College of Information and Computer Sciences; University of Memphis
Amherst
USA
trans.smcsystems.eic@gmail.comIEEE Account
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