Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems

Abbreviation

Publisher

IEEE

Journal Volumes

ISSN

2168-2216

Description

Filters

2013 - 201932020 - 20234
Reset filters

Search Results

Publications 1 - 7 of 7
  • Network Immunization Strategy by Eliminating Fringe Nodes: A Percolation Perspective
    Item type: Journal Article
    Liu, Gang; Deng, Yong; Cheong, Kang Hao (2023)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
    To date, many strategies involving graph theory have been proposed to solve the targeted immunization problem. Among them, the well-known relationship-related (RR) method makes use of the sum rule and the product rule from the perspective of the network explosive percolation. However, the RR method needs to carefully consider all nodes within a network, leading to high computational time. To close this gap, we propose the fringe node set: it is applied to an immunization strategy such as RR to remove noncritical nodes before optimizing the node sequence. Besides adapting this algorithm for strategies, such as RR and degree centrality strategy, we further propose a novel reconstruction method (RM) under the percolation perspective, which ranks critical nodes by measuring their contribution to the giant component in the network reconstruction or node reoccupying process. Experimental results based on our proposed identification method have demonstrated the feasibility of using the fringe node set. The competitive advantage of our proposed RM is also demonstrated in comparison with other existing methods.
  • A Nonlinear Model-Predictive Contouring Controller for Shared Control Driving Assistance in High-Performance Scenarios
    Item type: Journal Article
    Picotti, Enrico; Bruschetta, Mattia; Mion, Enrico; et al. (2023)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
    An increasing number of vehicles today are equipped with advanced driver-assistance systems that provide humans involved in the driving tasks with continuous and active support. State-of-the-art implementations of these systems frequently rely on an underlying vehicle controller based on the model-predictive control strategy. In this article, we propose a nonlinear model-predictive contouring controller for a driving assistance system in high-performance scenarios. The design follows specific features to ensure the effectiveness of the interaction, namely, adaptability with respect to the current vehicle state, high-performance driving capabilities, and tunability of the assistance system. First, the control algorithm performance is evaluated offline and compared with a commercial lap-time minimizer, then experimental implementation of the assistance system with the human driver (HD) in the loop has been accomplished on a professional dynamic driving simulator, where an evaluation of the specific features has been performed: 1) a gg-bound is exploited to adapt the controller's behavior to different driver abilities; 2) the controller's adaptability to unexpected HD behavior is tested; and 3) the controller's ability to handle the vehicle at the limit of maneuverability is established. The obtained strategy, then, demonstrates to be suitable as an underlying vehicle controller for a driver-assistance system on a racing track.
  • Modeling Belief Propensity Degree: Measures of Evenness and Diversity of Belief Functions
    Item type: Journal Article
    Zhou, Qianli; Bossé, Éloi; Deng, Yong (2023)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
    Based on Klir's framework of uncertainty, the total uncertainty (also called ambiguity) of belief function is linear addition of discord and nonspecificity. Though uncertainty measures of belief function have been discussed widely, there is no measure that can satisfy the monotonicity and range consistency properties at the same time. In this article, we discuss uncertainty measure of belief function from the perspective of information fractal dimension. An uncertainty quantity called evenness and its measure ${\rm Eve}$ are proposed, which can represent the belief propensity degree of belief function. We first propose the measures of diversity (normalized nonspecificity) and the element evenness (normalized discord), and then fuse them to calculate ${\rm Eve}$ . The proposed method can not only measure the subnormal mass function but also interpret the different views of Klir and Smets on "Uncertainty. " In addition, we extend Klir's framework of uncertainty based on the proposed information quantities.
  • Expected Convergence Rate to Consensus in Asymmetric Networks: Analysis and Distributed Estimation
    Item type: Journal Article
    Asadi, M. Mehdi; Khosravi, Mohammad; Aghdam, Amir G.; et al. (2020)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
    This paper investigates the expected rate of convergence to consensus in an asymmetric network represented by a weighted directed graph. The initial state of the network is represented by a random vector and the expectation is taken with respect to the random initial condition of the network. The proposed convergence rate is described in terms of the eigenvalues of the Laplacian matrix of the network graph. The generalized power iteration algorithm is then introduced based on the Krylov subspace method to compute the proposed expected convergence rate in a centralized fashion. To this end, the Laplacian matrix of the network is transformed to a new matrix such that existing techniques can be used to find the eigenvalue representing the expected convergence rate of the network. The convergence analysis of the centralized algorithm is performed with a prescribed upper bound on the approximation error of the algorithm. A distributed version of the centralized algorithm is then developed using the notion of consensus observer. The efficiency of the algorithms is subsequently demonstrated by simulations.
  • Manipulating Decision Making of Typical Agents
    Item type: Journal Article
    Yukalov, Vyacheslav I.; Sornette, Didier (2014)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
  • Quantitative Predictions in Quantum Decision Theory
    Item type: Journal Article
    Yukalov, Vyacheslav I.; Sornette, Didier (2018)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
  • Vulnerability of Smart Grids with Variable Generation and Consumption
    Item type: Journal Article
    Zio, Enrico; Sansavini, Giovanni (2013)
    IEEE Transactions on Systems, Man, and Cybernetics: Systems
Publications 1 - 7 of 7