Advances and Trends in Mathematical Modelling, Design, Control and Identification of Modern Vibrating Energy Conversion Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 4732

Special Issue Editors


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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
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Guest Editor
Faculty of Engineering, Universidad Panamericana Sede Guadalajara, Zapopan CP 45010, Mexico
Interests: power electronics; DC-DC converters; optimization of power electronics systems; modelling and control of power converters
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical Engineering (Guadalajara), Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City CP 45019, Mexico
Interests: analysis and control of electric power systems; applications of power electronics in electrical networks; optimization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S102TN, UK
Interests: behavioral system theory and dissipativity (higher-order modeling and control); nonlinear control design; modeling and control of power converters; power converter topology design; smart grid technologies; micro-synchrophasors (micro PMU); energy storage (battery modeling, balancing, state estimation and grid support applications)
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Special Issue Information

Dear Colleagues,

Vibrations or oscillations can be found in many modern energy conversion systems. Vibrations are mainly considered in mechanical structures, while oscillations can also be found in electrical, electronic, and electromechanical systems. The aim of this Special Issue is to introduce recent research contributions and trends in the fields of analysis, modelling, design, control, identification, and experimental instrumentation of energy conversion systems, where oscillations can be exhibited. The significant relevance of applied mathematics should be highlighted. In this context, novel experimental, theoretical and industrial studies related (but not limited) to wind energy, solar, chemical, electromechanical, electromagnetic energy conversion systems, including their components, and other applications of passive, semi-active, active and hybrid vibration control are welcome. Original research and review articles are welcome. Potential topics include, but are not limited to, mathematical modelling, vibration analysis and control, system identification, disturbance estimation, protection and control of modern power systems, power converters, power electronics, electric vehicles, battery energy storage systems, vibration isolation systems and other experimental and theoretical developments in which the presence of oscillations constitutes a relevant issue.

Prof. Dr. Francisco Beltran-Carbajal
Prof. Dr. Julio Cesar Rosas Caro
Dr. Juan M Ramirez
Dr. Jonathan C. Mayo-Maldonado
Guest Editors

Manuscript Submission Information

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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

  • mathematical modelling
  • analysis and control of oscillations
  • artificial intelligence in modern energy conversion systems
  • power electronics technologies
  • electric machinery
  • renewable energy conversion systems
  • system identification
  • harmonic distortion
  • experimental instrumentation
  • electric vehicles
  • electromagnetic systems

Published Papers (4 papers)

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Research

40 pages, 31758 KiB  
Article
Dynamical Sphere Regrouping Particle Swarm Optimization: A Proposed Algorithm for Dealing with PSO Premature Convergence in Large-Scale Global Optimization
by Martín Montes Rivera, Carlos Guerrero-Mendez, Daniela Lopez-Betancur and Tonatiuh Saucedo-Anaya
Mathematics 2023, 11(20), 4339; https://doi.org/10.3390/math11204339 - 19 Oct 2023
Cited by 2 | Viewed by 1655
Abstract
Optimizing large-scale numerical problems is a significant challenge with numerous real-world applications. The optimization process is complex due to the multi-dimensional search spaces and possesses several locally optimal regions. In response to this issue, various metaheuristic algorithms and variations have been developed, including [...] Read more.
Optimizing large-scale numerical problems is a significant challenge with numerous real-world applications. The optimization process is complex due to the multi-dimensional search spaces and possesses several locally optimal regions. In response to this issue, various metaheuristic algorithms and variations have been developed, including evolutionary and swarm intelligence algorithms and hybrids of different artificial intelligence techniques. Previous studies have shown that swarm intelligence algorithms like PSO perform poorly in high-dimensional spaces, even with algorithms focused on reducing the search space. However, we propose a modified version of the PSO algorithm called Dynamical Sphere Regrouping PSO (DSRegPSO) to avoid stagnation in local optimal regions. DSRegPSO is based on the PSO algorithm and modifies inertial behavior with a regrouping dynamical sphere mechanism and a momentum conservation physics effect. These behaviors maintain the swarm’s diversity and regulate the exploration and exploitation of the search space while avoiding stagnation in optimal local regions. The DSRegPSO mechanisms mimic the behavior of birds, moving particles similar to birds when they look for a new food source. Additionally, the momentum conservation effect mimics how birds react to collisions with the boundaries in their search space or when they are looking for food. We evaluated DSRegPSO by testing 15 optimizing functions with up to 1000 dimensions of the CEC’13 benchmark, a standard for evaluating Large-Scale Global Optimization used in Congress on Evolutionary Computation, and several journals. Our proposal improves the behavior of all variants of PSO registered in the toolkit of comparison for CEC’13 and obtains the best result in the non-separable functions against all the algorithms. Full article
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49 pages, 3291 KiB  
Article
Motion-Tracking Control of Mobile Manipulation Robotic Systems Using Artificial Neural Networks for Manufacturing Applications
by Daniel Galvan-Perez, Francisco Beltran-Carbajal, Ivan Rivas-Cambero, Hugo Yañez-Badillo, Antonio Favela-Contreras and Ruben Tapia-Olvera
Mathematics 2023, 11(16), 3489; https://doi.org/10.3390/math11163489 - 12 Aug 2023
Cited by 1 | Viewed by 852
Abstract
Robotic systems have experienced exponential growth in their utilization for manufacturing applications over recent decades. Control systems responsible for executing desired robot motion planning face increasingly stringent performance requirements. These demands encompass high precision, efficiency, stability, robustness, ease of use, and simplicity of [...] Read more.
Robotic systems have experienced exponential growth in their utilization for manufacturing applications over recent decades. Control systems responsible for executing desired robot motion planning face increasingly stringent performance requirements. These demands encompass high precision, efficiency, stability, robustness, ease of use, and simplicity of the user interface. Furthermore, diverse modern manufacturing applications primarily employ robotic systems within disturbed operating scenarios. This paper presents a novel neural motion-tracking control scheme for mobile manipulation robotic systems. Dynamic position output error feedback and B–Spline artificial neural networks are integrated in the design process of the introduced adaptive robust control strategy to perform efficient and robust tracking of motion-planning trajectories in robotic systems. Integration of artificial neural networks demonstrates performance improvements in the control scheme while effectively addressing common issues encountered in manufacturing environments. Parametric uncertainty, unmodeled dynamics, and unknown disturbance torque terms represent some adverse influences to be compensated for by the robust control scheme. Several case studies prove the robustness of the adaptive neural control scheme in highly coupled nonlinear six-degree-of-freedom mobile manipulation robotic systems. Case studies provide valuable insights and validate the efficacy of the proposed adaptive multivariable control scheme in manufacturing applications. Full article
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23 pages, 11893 KiB  
Article
A Simplified Model for the On-Line Identification of Bearing Direct-Dynamic Parameters Based on Algebraic Identification (AI)
by Saulo Jesús Landa-Damas, Jorge Colín-Ocampo, Andrés Blanco-Ortega, Arturo Abúndez-Pliego, José Gabriel Mendoza-Larios, Luis Alberto Baltazar-Tadeo and Demetrio Pérez-Vigueras
Mathematics 2023, 11(14), 3131; https://doi.org/10.3390/math11143131 - 15 Jul 2023
Cited by 1 | Viewed by 905
Abstract
In this paper, a mathematical model is presented to identify the direct dynamic coefficients (kxx, kzz, cxx, czz) of a pressurized bearing in a rotor-bearing system. The presented mathematical model for online identification is [...] Read more.
In this paper, a mathematical model is presented to identify the direct dynamic coefficients (kxx, kzz, cxx, czz) of a pressurized bearing in a rotor-bearing system. The presented mathematical model for online identification is the result of the application of the algebraic identification approach to a two-degree-of-freedom rotor-bearing model. The proposed identification model requires only the vibration response as the input data. The performance of the model was assessed by theoretically and experimentally testing the proposed identifier at different shaft frequencies and, for the experimental test, a pressurized bearing that has hydrodynamic and hydrostatic characteristics at a support pressure of 10 psi was considered. The working fluid is Chevron GST 32 oil. The results show negligible differences between the vibration response of the experimental rotor and those obtained numerically using the identified direct dynamic coefficients of the pressurized bearing. In addition, it is observed that the algebraic identifier determines the identified parameters in a time less than 0.2 s. The proposed identifier can be used in other types of bearings, which is a great advantage over other identifiers. Full article
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17 pages, 1589 KiB  
Article
On the Regulation of Wind Energy Conversion Systems Working as Conventional Generation Plants
by Irvin Lopez-Garcia, Cesar S. Lopez-Monsalvo, Oscar Gomez-Gonzalez, Mauricio Sanabria-Villamizar, Francisco Beltran-Carbajal and Rafael Escarela-Perez
Mathematics 2023, 11(11), 2495; https://doi.org/10.3390/math11112495 - 29 May 2023
Cited by 2 | Viewed by 853
Abstract
In this work, we obtain bounds for the wind speed interval in which a wind energy conversion system can be regulated in a similar manner to a conventional power generation plant. In particular, we conducted a steady-state analysis of a wind turbine coupled [...] Read more.
In this work, we obtain bounds for the wind speed interval in which a wind energy conversion system can be regulated in a similar manner to a conventional power generation plant. In particular, we conducted a steady-state analysis of a wind turbine coupled to a doubly fed induction generator (DFIG) that delivers power according to the electric grid requirements, and in a safe manner. In this sense, our main contribution is twofold. On the one hand, it involves expanding the secure operation window by adjusting the gearbox ratio, thus improving the reliability of the utility of grid integration. On the other hand, the WECS is controlled within new, safe wind speed intervals through a passivity-based controller and a proportional–integral controller, showing adequate performances in both cases. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Optimal selection of intrinsic mode functions applied in epilepsy-seizure detection
Authors: Luis Daladier Guerrero-Otoya; Maximiliano Bueno; Eduardo Giraldo; Marta Molinas
Affiliation: 1 Department of Electronics Instrumentation and Control, Faculty of Engineering, University of Cauca, Popayán, Colombia; 2 Department of Electrical Engineering, Faculty of Engineering, Technological University of Pereira, Pereira, Colombia; 3 Department of Engineering Cybernetics, Faculty of Engineering and Technology, NTNU, Trondheim, Norway
Abstract: Epilepsy is a severe chronic neurological disorder with considerable incidence due to recurrent epileptic seizures. These seizures can be noninvasive and diagnosed using electroencephalogram (EEG). The Empirical Mode Decomposition (EMD) has shown excellent results in the identification of epileptic crises. In this paper, a new approach is proposed to automatically select the most relevant intrinsic mode functions (IMFs), based on the use of the EMD, and a selection metrics analysis like the Minkowski distance, mean square error (MSE), cross-correlation, and entropy function. The aim is to choose the minimum number of IMFs to reconstruct the signals of the brain activity. The EEG signals were processed by EMD and the IMFs were chosen according the a set metrics selection. The IMFs with relevant information are selected for reconstruction of the EEG signal. To validate the results, the correlation coefficient, p-value, and Wasserstein metric were used, moreover, the EEGLAB software for mapping the brain activity of the EEG reconstructed and of the raw EEG original signal were used too.

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