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
06 September 2023
The neural network-based adaptive backstepping method is an effective tool to solve the cooperative tracking problem for nonlinear multiagent systems (MASs). However, this method cannot be directly extended to the case without continuous communication. It is because the discontinuous communication results in discontinuous signals in this case, the standard backstepping...
06 September 2023
In this article, the event-triggered fixed-time tracking control is investigated for uncertain strict-feedback nonlinear systems involving state constraints. By employing the universal transformed function (UTF) and coordinate transformation techniques into backstepping design procedure, the proposed control scheme ensures that all states are constrained within the time-varying asymmetric boundaries, and meanwhile,...
06 September 2023
It is an interesting open problem to enable robots to efficiently and effectively learn long-horizon manipulation skills. Motivated to augment robot learning via more effective exploration, this work develops task-driven reinforcement learning with action primitives (TRAPs), a new manipulation skill learning framework that augments standard reinforcement learning algorithms with formal...
06 September 2023
High-precision and safety control in face of disturbances and uncertainties is a challenging issue of both theoretical and practical importance. In this article, new adaptive anti-disturbance control schemes are proposed for a class of uncertain nonlinear systems with composite disturbances, including additive disturbances, multiplicative actuator faults, and implicit disturbances deeply...
01 September 2023
In this article, the output-feedback tracking control problem is considered for a class of nonlinear time-delay systems in a strict-feedback form. Based on a state observer with reduced order, a novel output-feedback control scheme is proposed using the backstepping approach, which is able to guarantee the system transient and steady-state...
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