Dynamics and Intelligent Control of Complex and Switched Systems

A special issue of Automation (ISSN 2673-4052).

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 7811

Special Issue Editors


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Guest Editor
Research and Development Department, National Institute for Research, Development and Testing in Electrical Engineering, ICMET Craiova, 200746 Craiova, Romania
Interests: SCADA control theory; electric drives
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Automatic Control and Electronics, University of Craiova, 200585 Craiova, Romania
Interests: adaptive systems; vibrational control; nonlinear control; power electronics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Automation, Electronics and Mechatronics, University of Craiova, 200585 Craiova, Romania
Interests: adaptive systems; vibrational control; nonlinear control; power electronics; automotive; embedded systems

Special Issue Information

Dear Colleagues,

Complex Systems processes can be described by nonlinear models of processes by using, for example, differential equations, and find key control applications in several industries such as energy systems, the automotive industry, aerospace engineering, biotechnology and so on.

A switched linear system is a hybrid/nonlinear system which consists of several linear subsystems and a switching rule that decides which of the subsystems are active at each moment in time. They are dynamical systems formed by a collection of linear continuous state models switching among them according to a discrete signal. These systems have shown to be useful for representing complex behaviors of physical systems interacting with logical rules or controllers. A switched system may be obtained from a hybrid system by neglecting the details of the discrete behavior and instead considering all possible switching patterns from a certain class.

Nowadays, it is a huge expectation concerning the use of various intelligent control techniques in order to control nonlinear and complex processes, in many cases with the emergence of advanced artificial intelligence. Intelligent control is in fact a computationally efficient procedure of guiding a complex system (uncertain, eventually with incomplete specifications) in an uncertain environment toward a certain goal. Therefore, an intelligent control technique needs learning of both the process and the environment to be a part of the control system. There are many definitions and classifications of intelligent control. However, it can be defined as a class of control techniques that use various artificial intelligence computing approaches such as neural networks, fuzzy logic, machine learning, evolutionary computation, genetic algorithms, etc.

This Special Issue proposes to bring together researchers, scientists and engineers from academia and industry so as to disseminate ideas and results related to the use of advanced techniques in the field of intelligent control of complex, nonlinear processes and switched systems.

Potential topics pertain, but are not limited, to intelligent control applied to Complex and Switched Systems:

  • Neural networks and fuzzy logic control;
  • Reinforcement learning-based control of nonlinear processes;
  • Deep-learning-based intelligent control;
  • Intelligent optimization and applications to nonlinear processes;
  • Intelligent modeling, identification and estimation of nonlinear processes;
  • Stability and robustness analysis of intelligent control systems;
  • New trends in intelligent control.

Theoretical and practical studies are equally encouraged. Application areas include energy systems (renewable energy, smart grids, electric drives), the automotive industry, aerospace engineering and biotechnology (including environmental systems and biomedical systems).

Dr. Marcel Nicola
Prof. Dr. Dan Selisteanu
Prof. Dr. Cosmin Ionete
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. Automation is an international peer-reviewed open access quarterly 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 1000 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

  • identification and estimation of complex processes
  • optimal control
  • distributed control
  • agent-based control
  • switched systems
  • reinforcement learning
  • neural networks and fuzzy logic control
  • stability and robustness

Published Papers (3 papers)

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Research

18 pages, 2920 KiB  
Article
Fuzzy Pressure Control: A Novel Approach to Optimizing Energy Efficiency in Series-Parallel Pumping Systems
by Thommas Kevin Sales Flores, Juan Moises Mauricio Villanueva and Heber Pimentel Gomes
Automation 2023, 4(1), 11-28; https://doi.org/10.3390/automation4010002 - 18 Jan 2023
Cited by 1 | Viewed by 2181
Abstract
Automation and control systems are constantly evolving, using artificial intelligence techniques to implement new forms of control, such as fuzzy control, with advantages over classic control strategies, especially in non-linear systems. Water supply networks are complex systems with different operating configurations, uninterrupted operation [...] Read more.
Automation and control systems are constantly evolving, using artificial intelligence techniques to implement new forms of control, such as fuzzy control, with advantages over classic control strategies, especially in non-linear systems. Water supply networks are complex systems with different operating configurations, uninterrupted operation requirements, equalization capacity and pressure control in the supply networks, and high reliability. In this sense, this work aims to develop a fuzzy pressure control system for a supply system with three possible operating configurations: a single motor pump, two motor pumps in series, or two motor pumps in parallel. For each configuration, an energy efficiency analysis was carried out according to the demand profile established in this case study. In order to validate the proposed methodology, an experimental water supply system was used, located in the Laboratory of Energy Efficiency and Hydraulics in Sanitation at the Federal University of Paraiba (LENHS/UFPB). Full article
(This article belongs to the Special Issue Dynamics and Intelligent Control of Complex and Switched Systems)
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28 pages, 15135 KiB  
Article
Control of PMSM Based on Switched Systems and Field-Oriented Control Strategy
by Marcel Nicola, Claudiu-Ionel Nicola, Dan Selișteanu and Cosmin Ionete
Automation 2022, 3(4), 646-673; https://doi.org/10.3390/automation3040033 - 10 Dec 2022
Cited by 3 | Viewed by 2598
Abstract
Starting from the problem of studying the parametric robustness in the case of the control of a permanent magnet-synchronous motor (PMSM), although robust control systems correspond entirely to this problem, due to the complexity of the algorithms of the robust type, in this [...] Read more.
Starting from the problem of studying the parametric robustness in the case of the control of a permanent magnet-synchronous motor (PMSM), although robust control systems correspond entirely to this problem, due to the complexity of the algorithms of the robust type, in this article the use of switched systems theory is proposed as a study option, given the fact that these types of systems are suitable both for the study of systems with variable structure and for systems with significant parametric variation under conditions of lower complexity of the control algorithms. The study begins by linearizing a PMSM model at a static operating point and continues with a systematic presentation of the basic elements and concepts concerning the stability of switched systems by applying these concepts to the control system of a PMSM based on the field-oriented control (FOC) strategy, which usually changes the value of its parameters during operation (stator resistance Rs, stator inductances Ld and Lq, but also combined inertia of PMSM rotor and load J). The numerical simulations performed in Simulink validate the fact that, for parametric variations of the PMSM structure, the PMSM control switched systems preserve qualitative performance in terms of its control. A series of Matlab programs are presented based on the YALMIP toolbox to obtain Pi matrices, by solving Lyapunov–Metzler type inequalities, and using dwell time to demonstrate stability, as well as the qualitative study of the performance of PMSM control switched systems by presenting in phase plane and state space analysis of the evolution of state vectors: ω PMSM rotor speed, iq current, and id current. Full article
(This article belongs to the Special Issue Dynamics and Intelligent Control of Complex and Switched Systems)
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27 pages, 11431 KiB  
Article
Speed Control Based on State Vector Applied for Electrical Drive with Elastic Connection
by Mateusz Malarczyk, Mateusz Zychlewicz, Radoslaw Stanislawski and Marcin Kaminski
Automation 2022, 3(3), 337-363; https://doi.org/10.3390/automation3030018 - 13 Jul 2022
Cited by 7 | Viewed by 2131
Abstract
The paper is focused on issues related to the control of electrical drives with oscillations of state variables. The main problem deals with the construction of the mechanical part, which contains elastic elements used as a coupling between the motor machine and the [...] Read more.
The paper is focused on issues related to the control of electrical drives with oscillations of state variables. The main problem deals with the construction of the mechanical part, which contains elastic elements used as a coupling between the motor machine and the load. In such cases, strict tracking of the reference trajectory is difficult, so damping of the disturbances is necessary. For this purpose, the full state vector of the object is applied as the feedback signal for the speed controller. This method is efficient and relatively easy to implement (including the hardware part). However, the control accuracy is dependent on the quality of the parameters identification and the invariance of the object. Thus, two adaptive structures are proposed for the two-mass system. Moreover, selected coefficients were optimized using metaheuristic algorithms (symbiotic organism search and flower pollination algorithm). After presentation of the preliminaries and mathematical background, tests were conducted, and the numerical simulations are shown. Finally, the experimental verification for the 0.5 kW DC machines was performed. The results confirm the theoretical concept and the initial assumptions: the state controller leads to the precise control of the drive with a long shaft; recalculation of the parameters can improve the work of the drive under changes of time constants; modern design tools are appropriate for this application. Full article
(This article belongs to the Special Issue Dynamics and Intelligent Control of Complex and Switched Systems)
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