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
08 April 2026
Concurrent and complex aerial missions with multiple targets exceed the capabilities of a single cooperative formation of high-speed flight vehicles (HSFVs). To address this challenge, this article decomposes a fleet of HSFVs (subject to multiple compounding factors, including unknown aerodynamic disturbances, unmodeled or parametric uncertainties, actuator faults, and potential intervehicle...
05 June 2026
This article investigates the prescribed-time fault-tolerant cooperative control problem for second-order nonlinear heterogeneous multiagent systems (MASs) subject to multiple actuator faults. A novel prescribed-time stability criterion, independent of time-varying gain functions, is established to facilitate convergence analysis. Fuzzy neural networks (FNNs) are employed to approximate the unknown heterogeneous nonlinear dynamics,...
28 May 2026
High penetration of inverter-based renewables introduces pronounced volatility and heterogeneity to power systems. Coordinating heterogeneous frequency regulation units (FRUs) for robust load frequency control (LFC) remains challenging due to their disparate dynamics and capacities. To improve the frequency regulation capability of FRUs, an adaptive fractional-order error-based active disturbance rejection control...
21 May 2026
Output regulation is a fundamental problem in control theory, extensively studied since the 1970s. Traditionally, research has primarily addressed scenarios where the system model is explicitly known, leaving the problem in the absence of a system model less explored. Leveraging recent advances in Willems et al.’s fundamental lemma, data-driven control...
03 March 2026
This article addresses the problem of resilient consensus control for nonlinear multiagent systems (MASs) operating over networks subject to denial-of-service (DoS) attacks. We propose an event-triggered, recurrent-neural-network-based model predictive consensus controller (RNN-MPCC) that integrates three components: 1) a data-driven recurrent neural network (RNN) predictor of agent dynamics with a certified...
03 March 2026
The problem of command-filter-based adaptive fixed-time tracking control is investigated for nonlinear systems with time-varying uncertain parameters and disturbances in this article. Existing fixed-time control strategies via an adaptive approach are primarily bounded-error, trajectory tracking-oriented. Different from previous results, we propose a new fixed-time stability lemma utilizing an exponential decay...
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