Transactions on SMC: Systems


The scope of the IEEE Transactions on Systems, Man, and Cybernetics: Systems includes the field of systems engineering. It also includes issue formulation, analysis and modeling, decision making, and issue interpretation for any of the systems engineering lifecycle phases associated with the definition, development, and deployment of large systems. Other topics include systems management, systems engineering processes, and a variety of systems engineering methods such as optimization, modeling and simulation.

IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans was renamed IEEE Transactions on Systems, Man, and Cybernetics: Systems on January 1, 2013.

Posting Preprints to Non-IEEE Servers

Authors should disclose postings on approved preprint services when submitting papers to SMCS Journals.

Consult relevant sections posted here.

The following statement must be included on the initial screen of the preprint site:

“This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.”

Upon acceptance of the article by IEEE, the preprint article must be replaced with the accepted version, as described in the section “Accepted article.”


Robert Kozma, Editor-In-Chief
Robert Kozma

FedEx Institute of Technology
Department of Mathematics
University of Memphis
Memphis, TN 38152, USA


16 May 2024
16 May 2024
08 March 2024
Batch processes are typically nonlinear systems with constraints. Model predictive control (MPC) and iterative learning control (ILC) are effective methods for controlling batch processes. By combining batch-wise ILC and time-wise MPC, this article proposes a multirate control scheme for constrained nonlinear systems. Two-dimensional (2-D) framework is used to combine historical...
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05 April 2024
In this article, for the single-input–single-output (SISO) nonlinear strict-feedback system, optimized backstepping (OB) control combined with the dynamic surface (DS) technique is developed. OB is to make every subsystem control of backstepping as the optimized one so as to ensure the entire backstepping control being optimized. However, the original design...
26 March 2024
We present differentiable predictive control (DPC), a method for offline learning of constrained neural control policies for nonlinear dynamical systems with performance guarantees. We show that the sensitivities of the parametric optimal control problem can be used to obtain direct policy gradients. Specifically, we employ automatic differentiation (AD) to efficiently...
13 February 2024
Distributed optimization achieves a minimized objective function through collaboration among distributed agents. Considering limited communication capabilities and privacy concerns, this article proposes a dynamic event-triggered differentially private gradient-tracking algorithm for distributed optimization. The communication requirement is reduced by event triggering, while the $epsilon $ -differential privacy is guaranteed by perturbations...
06 February 2024
The security problem for a kind of switched nonlinear systems with denial-of-service (DoS) attacks is addressed here with a novel event-triggered neural network (NN) adaptive control technique. The provided event-triggered control algorithm, compared to the current output feedback control schemes on continuous-time systems, not only conserves communication resources but also...
06 February 2024
This article addresses the problem of optimal sensor selection for diagnosability enforcement of discrete event systems modeled with Petri nets. Given a nondiagnosable labeled Petri net labeled Petri net (LPN) that may reach deadlocks, it can be enforced to be diagnosable by a novel systematic strategy through a mask labeling...

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