IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans最新文献

{"title":"A Nesterov-Like Gradient Tracking Algorithm for Distributed Optimization Over Directed Networks","authors":"Qingguo Lü, X. Liao, Huaqing Li, Tingwen Huang","doi":"10.1109/TSMC.2019.2960770","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2960770","url":null,"abstract":"In this article, we concentrate on dealing with the distributed optimization problem over a directed network, where each unit possesses its own convex cost function and the principal target is to minimize a global cost function (formulated by the average of all local cost functions) while obeying the network connectivity structure. Most of the existing methods, such as push-sum strategy, have eliminated the unbalancedness induced by the directed network via utilizing column-stochastic weights, which may be infeasible if the distributed implementation requires each unit to gain access to (at least) its out-degree information. In contrast, to be suitable for the directed networks with row-stochastic weights, we propose a new directed distributed Nesterov-like gradient tracking algorithm, named as D-DNGT, that incorporates the gradient tracking into the distributed Nesterov method with momentum terms and employs nonuniform step-sizes. D-DNGT extends a number of outstanding consensus algorithms over strongly connected directed networks. The implementation of D-DNGT is straightforward if each unit locally chooses a suitable step-size and privately regulates the weights on information that acquires from in-neighbors. If the largest step-size and the maximum momentum coefficient are positive and small sufficiently, we can prove that D-DNGT converges linearly to the optimal solution provided that the cost functions are smooth and strongly convex. We provide numerical experiments to confirm the findings in this article and contrast D-DNGT with recently proposed distributed optimization approaches.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"135 1","pages":"6258-6270"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89663183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Community Evolution Analysis Framework for Large-Scale Complex Networks Based on Strong and Weak Events","authors":"Shaojie Qiao, Nan Han, Yunjun Gao, Ronghua Li, Jianbin Huang, Heli Sun, Xindong Wu","doi":"10.1109/TSMC.2019.2960085","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2960085","url":null,"abstract":"Community evolution remains a heavily researched and challenging area in the analysis of dynamic complex network structures. Currently, the primary limitation of traditional event-based approaches for community evolution analysis is the lack of strict constraint conditions for distinguishing evolutionary events, which entails that as the cardinality of discovered events increases, so does the number of redundant events. Another limitation of existing approaches is the lack of consideration for weak events. Weak events can be generated by small changes in communities, which are empirically prevalent, and are typically not captured by traditional events. To manage these two aforementioned limitations, this research aims to formalize a weak and strong events-based framework, which includes the following newly discovered events: “weak shrink,” “weak expand,” “weak merge,” and “weak splity” predicated on the community overlapping degree and community degree membership, this article refines these traditional strong events, as well as new constraints for weak events. In addition, a community evolution mining framework, which is based on both strong and weak events, is proposed and denoted by a weak-event-based community evolution method (WECEM). The framework can be summarized by the following: 1) communities in complex networks with adjacent time-stamps are compared to determine the community overlapping degree and community membership degree; 2) the values of the community overlapping degree and membership degree meet the definition of events; and 3) weak events are effectively identified. Extensive experimental results, on real and synthetic data sets consisting of dynamic complex networks and online social networks, demonstrate that WECEM is able to identify weak events more effectively than traditional frameworks. Specifically, WECEM outperforms traditional frameworks by 22.9% in the number of discovered strong events. The detection accuracy of evolutionary events is approximately 12.2% higher than that of traditional event-based frameworks. It is also worth noting that, as the cardinality of the data grows, the proposed framework, when compared with traditional frameworks, can more effectively, and efficiently, mine large-scale complex networks.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"34 1","pages":"6229-6243"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74443218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robustness Evaluation of Multipartite Complex Networks Based on Percolation Theory","authors":"Qing Cai, S. Alam, Mahardhika Pratama, Jiming Liu","doi":"10.1109/TSMC.2019.2960156","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2960156","url":null,"abstract":"To investigate the robustness of complex networks in face of disturbances can help prevent potential network disasters. Percolation on networks is a potent instrument for network robustness analysis. However, existing percolation theories are primarily developed for interdependent or multilayer networks. Little attention is paid to multipartite networks which are an indispensable part of complex networks. In this article, we theoretically explore the robustness of multipartite networks under node failures. We put forward the generic percolation theory for gauging the robustness of multipartite networks with arbitrary degree distributions. Our developed theory is capable of quantifying the robustness of multipartite networks under either random or target node attacks. Our theory unravels the second order phase transition phenomenon for multipartite networks. In order to verify the correctness of the proposed theory, simulations on computer generated multipartite networks have been carried out. The experiments demonstrate that the simulation results coincide quite well with that yielded by the proposed theory.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"1995 1","pages":"6244-6257"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88109853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Dynamic Event-Triggered Control Approach to Leader-Following Consensus for Linear Multiagent Systems","authors":"Dan Liu, Guanghong Yang","doi":"10.1109/TSMC.2019.2960062","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2960062","url":null,"abstract":"This article focuses on the leader-following consensus for linear multiagent systems under a directed communication topology. A novel dynamic event-triggered mechanism is put forward to schedule the interagent communication. It removes the assumption that each agent has to broadcast continuously, and therefore resource consumption is reduced significantly. Different from the existing event-triggered mechanisms, the proposed mechanism involves internal dynamic variables that play an important role in excluding Zeno behavior. Then, an event-based distributed control protocol is developed by using locally triggering data. It is proven that the leader-following consensus is achieved under our control strategy. Moreover, the criterion for designing a desired triggered mechanism and the control protocol is derived in terms of linear matrix inequalities. Numerical simulations demonstrate that the proposed strategy is capable of reducing communication more effectively than the existing results.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"23 1","pages":"6271-6279"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87875642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Auto-Adjustable and Time-Consistent Model for Determining Coagulant Dosage Based on Operators’ Experience","authors":"Y. Liu, Yiwei He, Shumao Li, Zhenghui Dong, Junping Zhang, U. Kruger","doi":"10.1109/TSMC.2019.2956647","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2956647","url":null,"abstract":"This article examines how to automate the determination of the coagulant dosage for water treatment plants. Whilst most of the processes for water treatment are automated, determining the coagulant dosage, required for reducing turbidity, depends on well-trained and experienced operators. Based on a time-series data set provided by the Shanghai municipal investment water production company, this article comprehensively surveys existing coagulant prediction methods and utilizes an auto-adjustable and time-consistent model to incorporate the operators’ experience. Compared to existing methods, the algorithm introduced in this article produced a better accuracy for predicting the coagulant dosage. Moreover, this article demonstrates that taking seasonal effects into account can approximate operator behavior more accurately. To examine the robustness of the identified models, this article examines the model performance based on water drawn from different locations/sources.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"23 1","pages":"5614-5625"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74053776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extended Dissipativity-Based Control for Hidden Markov Jump Singularly Perturbed Systems Subject to General Probabilities","authors":"Feng Li, Shengyuan Xu, Hao Shen, Zhengqiang Zhang","doi":"10.1109/TSMC.2019.2957659","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2957659","url":null,"abstract":"This article deals with the extended dissipativity-based control issue for singularly perturbed systems (SPSs) with Markov jump parameters, in which the partial information issues of the Markov chain are fully considered. A comprehensive hidden Markov model (HMM) is established for the partial information issues on Markov chain, in which the transition probabilities of the hidden Markov state and the observation probabilities of the observed state are general, that is, the uncertainty and the unknown peculiarity of them may be encountered simultaneously. By using the HMM with general probabilities, a comprehensive criterion is derived to analyze the extended stochastic dissipativity of the hidden Markov jump SPSs with the different partial information issues on the Markov chain. Based on the derived criterion, an explicit expression to acquire the desired HMM-based controller is presented. An illustrative example and a vehicle active suspension system are, finally, show the validity of the established theoretical results.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"114 1","pages":"5752-5761"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79344282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Event-Triggered and Double-Quantized Consensus of Leader–Follower Multiagent Systems With Semi-Markovian Jump Parameters","authors":"Cheng Gong, Guopu Zhu, P. Shi","doi":"10.1109/TSMC.2019.2957530","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2957530","url":null,"abstract":"In practice, many dynamical systems can be modeled by multiagent systems (MASs) with different operating modes. The consensus problem of leader–follower MASs with semi-Markovian jump parameters is investigated in this article. First, to save the bandwidth resources of the MASs, adaptive event-triggered communication and double quantization are introduced to design the consensus protocol, in which the event-triggered threshold is dynamically adjusted instead of being a constant, and not only the data from the agents to the consensus controller but also that from the controller to the agents, are both quantized. Next, a sufficient condition is established to ensure the stability of the consensus error system under the adaptive event-triggered condition, and then the consensus controller is developed by matrix inequality approach. Finally, a numeral example is given to demonstrate the effectiveness of the developed consensus controller.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"10 1","pages":"5867-5879"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82724003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Network-Based Sampled-Data Control for Switched Uncertain Nonlinear Systems","authors":"Shi Li, C. Ahn, Jian Guo, Z. Xiang","doi":"10.1109/TSMC.2019.2954231","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2954231","url":null,"abstract":"This article investigates the sampled-data stabilization problem of a class of switched nonlinear systems. All subsystems of the considered system are allowed to be unstabilizable. To relax the restrictions on unknown nonlinear functions in some existing results, we use the nonlinear approximation ability of radial basis function neural networks. Novel mode-dependent adaptive laws and sampled-data control laws are constructed by only using the system states’ information at sampling instants. A novel sampled-data switching condition is derived, which can avoid Zeno behavior effectively. To guarantee that all states of the closed-loop system (CLS) are bounded, a new allowable sampling period is deduced. Finally, we demonstrate the proposed method’s effectiveness through two examples.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"60 1","pages":"5437-5445"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82945187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristic Modeling Approach for High-Order Linear Dynamical Systems","authors":"Lei Chen, Xinghuo Yu, Changyin Sun","doi":"10.1109/TSMC.2019.2956484","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2956484","url":null,"abstract":"This article presents a full mathematical proof of the characteristic modeling approach for high-order linear dynamical systems. It explores the nature of the characteristic model in rigorous mathematical forms, also showing why and how the high-order dynamics can be compressed into the lower-order characteristic model. The relationships between high-order linear continuous dynamical systems, discrete-time characteristic model coefficients, and sampling-time intervals are investigated.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"33 1-2 1","pages":"5405-5413"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78208974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ensemble Learning Based Brain–Computer Interface System for Ground Vehicle Control","authors":"Jiayu Zhuang, Keke Geng, Guo-dong Yin","doi":"10.1109/TSMC.2019.2955478","DOIUrl":"https://doi.org/10.1109/TSMC.2019.2955478","url":null,"abstract":"This article establishes a novel electroencephalograph (EEG)-based brain–computer interface (BCI) system for ground vehicle control with potential application of mobility assistance to the disabled. To enable an intuitive motor imagery (MI) paradigm of “left,” “right,” “push,” and “pull,” a driving simulator based EEG data recording and automatic labeling platform is built for dataset making. In the preprocessing stage, a wavelet and canonical correlation analysis (CCA) combined method is used for artifact removal and improving signal-to-noise ratio. An ensemble learning based training and testing framework is proposed for MI EEG data classification. The average classification accuracy of proposed framework is about 91.75%. This approach essentially takes advantage of the common spatial pattern (CSP) with ability of extracting the feature of event-related potentials and the convolutional neural networks (CNNs) with powerful capacity of feature learning and classification. To convert the classification results of EEG data segments into motion control signals of ground vehicle, shared control strategy is used to realize the control command of “left-steering,” “right-steering,” “acceleration,” and “stop” considering collision avoidance with obstacles detected by a single-line LIDAR. The online experimental results on a model vehicle platform validate the significant performance of the established BCI system and reveal the application potential of BCI on the vehicle control and automation.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"68 1","pages":"5392-5404"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90450794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}