Scope
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or between machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
IEEE Transactions on Cybernetics replaced the IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics on January 1, 2013.
Editor-in-Chief
Peng Shi
Editor-In-Chief
School of Electrical and Electronic Engineering,
The University of Adelaide, Australia
Articles
18 November 2024
This article addresses the collision avoidance and formation control problem for multisatellite systems. A novel safe reinforcement learning (RL) algorithm based on an adaptive dynamic programming framework is proposed. The highlights of the algorithm are the adaptive distance-varying learning method to integrate online data with historical data and the usage...
14 November 2024
This article investigates a comprehensive data-driven event-triggered secure lateral control of autonomous vehicles under actuator attacks. We consider stabilization issues of autonomous vehicles subject to modeling difficulties, limited communication resources, and actuator attacks. The dynamic model decomposition (DMD) from data is exploited to characterize the inherent lateral dynamics model of...
04 November 2024
Traditional reinforcement learning (RL) methods for optimal control of nonlinear processes often face challenges, such as high computational demands, long training times, and difficulties in ensuring the safety of closed-loop systems during training. To address these issues, this work proposes a safe transfer RL (TRL) framework. The TRL algorithm leverages...
30 October 2024
The enhancement of underwater images has emerged as a significant technological challenge in advancing marine research and exploration tasks. Due to the scattering of suspended particles and absorption of light in underwater environments, underwater images tend to present blurriness and predominantly color distortion. In this study, we propose a novel...
24 September 2024
This article dedicates to investigating a methodology for enhancing adaptability to environmental changes of reinforcement learning (RL) techniques with data efficiency, by which a joint control protocol is learned using only data for multiagent systems (MASs). Thus, all followers are able to synchronize themselves with the leader and minimize their...
24 September 2024
Fully actuated system (FAS) approach was proposed in 2020 and 2021 as a general framework for control system analysis and design based on a newly discovered general type of fully actuated models for dynamical systems. Due to its great advantages and power in dealing with complicated nonlinear time-varying and time-delay...
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