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Mathematics
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Advanced Control Systems and Engineering Cybernetics
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Advanced Control Systems and Engineering Cybernetics

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".

Deadline for manuscript submissions: 20 July 2025 | Viewed by 1789

Special Issue Editors

Prof. Dr. David Sotelo

E-Mail Website
Guest Editor
Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
Interests: optimal and robust control; process identification and design of control structures
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Carlos Sotelo

E-Mail Website
Guest Editor
Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
Interests: optimal and robust control; process identification and design of control structures
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Francisco Beltran-Carbajal

E-Mail Website
Guest Editor
Departamento de Energía, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Mexico City 02200, Mexico
Interests: vibration control; system identification; rotating machinery; mechatronics; automatic control of energy conversion systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Control theory is ubiquitous in engineering cybernetics today, and many applications of this technology are being developed in a broad range of areas, especially research on the science of automatic control and supervision of dynamic systems, such as robots, aircraft, marine craft, cars, electrical circuits, biological systems, and process plants. Moreover, in recent years, these areas have been generating interest for including adaptation, learning, self-organization, pattern recognition, and artificial intelligence. The primary objective of this Special Issue, titled “Advanced Control Systems and Engineering Cybernetics”, is to collect the cutting-edge technological trends and challenges in the field of control theory, providing significant theoretical support and practical methodologies for addressing actual problems in cybernetic engineering applications to transform our society in many ways, improving healthcare, education, transportation, manufacturing, ethical implications, and safety concerns. In light of the abovementioned applications, contributors are invited to submit their original manuscripts on topics including, but not limited to:

  • Real-world control theory applications.
  • Modeling, control, and optimization of complex systems.
  • Robust constrained cooperative control schemes.
  • Neural networks and deep learning.
  • Reinforcement learning, continual learning, domain adaptation.
  • Machine learning for image processing.
  • Multi-agent collaborative control for manufacturing.
  • Artificial intelligence for optimization.

The guest editors look forward to receiving your contributions to this Special Issue. Let us continue to push the advances of control theory in engineering cybernetics.

Prof. Dr. David Sotelo
Prof. Dr. Carlos Sotelo
Prof. Dr. Francisco Beltran-Carbajal
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Mathematics is an international peer-reviewed open access semimonthly 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

  • autonomous vehicles
  • mobile robots
  • control systems and optimization
  • obstacle avoidance
  • learning and adaptive control
  • artificial intelligence
  • multi-agent systems

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Published Papers (2 papers)

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18 pages, 1555 KiB  
Article
State Observer for Time Delay Systems Applied to SIRS Compartmental Epidemiological Model for COVID-19
by Raúl Villafuerte-Segura, Jorge A. Hernández-Ávila, Gilberto Ochoa-Ortega and Mario Ramirez-Neria
Mathematics 2024, 12(24), 4004; https://doi.org/10.3390/math12244004 - 20 Dec 2024
Viewed by 827
Abstract
This manuscript presents a Luenberger-type state observer for a class of nonlinear systems with multiple delays. Sufficient conditions are provided to ensure practical stability of the error dynamics. The exponential decay of the observation error dynamics is guaranteed through the use of Lyapunov–Krasovskii [...] Read more.
This manuscript presents a Luenberger-type state observer for a class of nonlinear systems with multiple delays. Sufficient conditions are provided to ensure practical stability of the error dynamics. The exponential decay of the observation error dynamics is guaranteed through the use of Lyapunov–Krasovskii functionals and the feasibility of linear matrix inequalities (LMIs). Additionally, a time delay SIRS compartmental epidemiological model is introduced, where the time delays correspond to the transition rates between compartments. The model considers that a portion of the recovered population becomes susceptible again after a period that follows its recovery. Three time delays are considered, representing the exchange of individuals between the following compartments: τ1,2,3, the time it takes for an individual to recover from the disease, the time it takes for an individual to lose immunity to the disease, and the incubation period associated to the disease. It is shown that the effective reproduction number of the model depends on the rate at which the susceptible population becomes infected and, after a period of incubation, starts to be infectious, and the fraction of the infectious that recovers after a a certain period of time. An estimation problem is then addressed for the resulting delay model. The observer is capable of estimating the compartmental populations of Susceptible S(t) and Recovered R(t) based solely on the real data available, which correspond to the Infectious population Ir(t). The Ir(t) data used for the state estimation are from a 55-day period of the pandemic in Mexico, reported by the World Health Organization (WHO), before vaccination. Full article
(This article belongs to the Special Issue Advanced Control Systems and Engineering Cybernetics)
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22 pages, 4068 KiB  
Article
Trajectory Tracking of a 2-Degrees-of-Freedom Serial Flexible Joint Robot Using an Active Disturbance Rejection Controller Approach
by Mario Ramŕez-Neria, Gilberto Ochoa-Ortega, Alejandro Toro-Ossaba, Eduardo G. Hernandez-Martinez, Alexandro López-González and Juan C. Tejada
Mathematics 2024, 12(24), 3989; https://doi.org/10.3390/math12243989 - 18 Dec 2024
Viewed by 661
Abstract
This paper presents the development of an Active Disturbance Rejection Controller (ADRC) to address the trajectory tracking problem of a 2DOF (Degrees of Freedom) Serial Flexible Robot. The proposed approach leverages differential flatness theory to determine the system’s flat output, simplifying the trajectory [...] Read more.
This paper presents the development of an Active Disturbance Rejection Controller (ADRC) to address the trajectory tracking problem of a 2DOF (Degrees of Freedom) Serial Flexible Robot. The proposed approach leverages differential flatness theory to determine the system’s flat output, simplifying the trajectory tracking problem into a linear state feedback control with disturbance rejection. A set of a Generalized Proportional Integral Observer (GPIO) and Luenberger observers is employed to estimate the derivatives of the flat output and both internal and external disturbances in real time. The control law is experimentally validated on a 2DOF Serial Flexible Robot prototype developed by Quanser. Quantitative results demonstrate that the ADRC achieves superior performance compared to a partial state feedback control scheme, with a Mean Squared Error (MSE) as low as 1.0651 × 10−5 rad2 for trajectory tracking. The ADRC effectively suppresses oscillations, minimizes high-frequency noise and reduces saturation effects, even under external disturbances. These findings underscore the robustness and efficiency of the proposed method for underactuated flexible systems. Full article
(This article belongs to the Special Issue Advanced Control Systems and Engineering Cybernetics)
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