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Entropy
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Information Theory in Control Systems, 3rd Edition
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Information Theory in Control Systems, 3rd Edition

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 20 May 2026 | Viewed by 1038

Special Issue Editor

Prof. Dr. Adrian-Mihail Stoica

E-Mail Website
Guest Editor
Faculty of Aerospace Engineering, National University of Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania
Interests: control systems; optimal control; estimation and filtering; robust control; stochastic systems; fault detection and isolation; automatic flight control systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

An important area of investigation in control science is that of networked multi-agent systems. Information between agents is exchanged through communication channels subject to various imperfections, including delayed transmissions, lost packets, data quantization, and decentralized architectures. Achieving the interaction between control systems and information theory has thus become a challenging task and has received extensive attention over recent years.

The aim of this Special Issue is to present new theoretical developments and potential applications bridging the domains of control, communications, and information theory.

Topics may include, but are not restricted to, the following:

  • Networked control systems under communication constraints;
  • Entropy estimation and filtering theory for multi sensor systems;
  • Sampled-data control for networked control systems;
  • Entropy minimization and optimal control;
  • Stochastic optimal control with randomized control strategies;
  • Feedback control, state estimation, and consensus problems for multi-agent systems;
  • Fault-tolerant control design for networked control systems with communication constraints;
  • Entropy optimization in aerospace engineering applications;
  • Feedback control under fading communication channels;
  • New algorithms and numerical procedures for entropy optimization.

Prof. Dr. Adrian-Mihail Stoica
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multi-agent systems
  • optimal control
  • optimal estimation and filtering
  • communication channel constraints
  • decentralized control
  • fault detection
  • isolation and recovery

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Related Special Issues

Published Papers (2 papers)

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Research

12 pages, 488 KB  
Article
State Feedback Optimal L2-Induced Control of Nonlinear Systems Utilizing Universal Approximation
by Adrian-Mihail Stoica and Isaac Yaesh
Entropy 2026, 28(5), 531; https://doi.org/10.3390/e28050531 - 7 May 2026
Viewed by 100
Abstract
This paper presents an optimal L2-induced control problem for systems with multiple sector-bounded nonlinearities. Sufficient boundedness conditions for the L2-induced norm are derived in terms of a specific system of linear matrix inequalities (LMIs). Based on these conditions, an [...] Read more.
This paper presents an optimal L2-induced control problem for systems with multiple sector-bounded nonlinearities. Sufficient boundedness conditions for the L2-induced norm are derived in terms of a specific system of linear matrix inequalities (LMIs). Based on these conditions, an optimal state feedback control problem is then formulated and solved for the considered class of nonlinear systems. A procedure to reduce the conservatism of the derived conditions is also provided. The proposed formulation, which explicitly considers multiple sector-bounded nonlinearities, is useful because it enables optimal L2-control problems for a much wider class of nonlinearities. Indeed, by invoking the universal approximation theorem, one may represent nonlinearities that do not satisfy sector-bounded conditions as a weighted sum of sector-bounded sigmoid functions. The theoretical and procedural developments are illustrated by a numerical example consisting of the state feedback optimal L2-induced control of a forced van der Pol oscillator. Full article
(This article belongs to the Special Issue Information Theory in Control Systems, 3rd Edition)
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33 pages, 630 KB  
Article
PID Control for Uncertain Systems with Integral Measurements and DoS Attacks Using a Binary Encoding Scheme
by Nan Hou, Yanshuo Wu, Hongyu Gao, Zhongrui Hu and Xianye Bu
Entropy 2026, 28(2), 225; https://doi.org/10.3390/e28020225 - 15 Feb 2026
Viewed by 445
Abstract
In this paper, an observer-based proportional-integral-derivative (PID) controller is designed for a class of uncertain nonlinear systems with integral measurements, denial-of-service (DoS) attacks and bounded stochastic noises under a binary encoding scheme (BES). Parameter uncertainty is involved with a norm-bounded multiplicative expression. Integral [...] Read more.
In this paper, an observer-based proportional-integral-derivative (PID) controller is designed for a class of uncertain nonlinear systems with integral measurements, denial-of-service (DoS) attacks and bounded stochastic noises under a binary encoding scheme (BES). Parameter uncertainty is involved with a norm-bounded multiplicative expression. Integral measurements are considered to reflect the delayed signal collection of sensor. For communication, BES is put into use in the signal transmission process from the sensor to the observer and from the controller to the actuator. Random bit flipping is described that may take place caused by channel noises, whose impact is described by a stochastic noise. Randomly occurring DoS attacks are taken account of that may appear due to the shared network, which block the transmitted signals totally. Three sets of Bernoulli-distributed random variables are adopted to reveal the random occurrence of uncertainties, bit flipping and DoS attacks. The aim of this paper is to design an observer-based PID controller which guarantees that the closed-loop system reaches exponential ultimate boundedness in mean square (EUBMS). By virtue of Lyapunov stability theory, stochastic analysis technique and matrix inequality method, a sufficient condition is developed for designing the observer-based PID controller such that the closed-loop system achieves EUBMS performance, and the ultimate upper bound of the controlled output is bounded and such a bound is minimized. The gain matrices of the observer-based controller are acquired explicitly by virtue of solving the solution to an optimized issue with several matrix inequality constraints. Two simulation examples are given which indicate the usefulness of the proposed control method in this paper adequately. Full article
(This article belongs to the Special Issue Information Theory in Control Systems, 3rd Edition)
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