Actuators for Identification, Vibration Analysis, and Control of Mechatronic Systems

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Control Systems".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 4105

Special Issue Editor


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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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Special Issue Information

Dear Colleagues,

It is well-known that the design of innovative strategies for efficient operation, robust control, effective suppression of undesirable oscillations and real-time identification for modern mechatronic systems, as well as for their multiple components, involves several open and challenging research topics. In this context, actuators constitute a fundamental part of the automatic control, vibration analysis and system identification of a wide range of applications of modern mechatronic systems, such as aerial robots, collaborative robots, exoskeletons, active and semi-active vibration control and electric, hybrid and autonomous cars. Moreover, undesirable vibrations or oscillations can be exhibited in several electric, electronic and mechanical components of mechatronic systems. The real-time estimation of system parameters and disturbances can be used for the synthesis of new high-efficiency robust control techniques and fault detection and diagnosis. Controlled electric motors can be used as efficient motion actuators in many engineering systems. Multiple-pulse electronic converters topologies can be employed as actuators for efficient control implementation as well.

This Special Issue aims to present recent and innovative contributions on modeling, system identification, vibration analysis, diverse automatic control design methodologies and applications of actuators for a wide variety of recent mechatronics systems, including their electric, electronic and mechanical components and software engineering. Thus, in this context, we welcome important recent contributions related (but not limited) to modeling, vibration control, system identification, vehicle suspensions, collaborative robotic systems, autonomous aerial and underwater vehicles and other experimental and theoretical results in this very broad matter, where the science and technology of actuators and control systems play a relevant role.

According to the scope of Actuators, this Special Issue explicitly considers theoretical and experimental contributions on actuators and control systems in several challenging open research issues for efficient operation, robust control, effective suppression of undesirable oscillations and real-time identification for modern mechatronic systems, as well as for their multiple components.

Prof. Dr. Francisco Beltran-Carbajal
Guest Editor

Manuscript Submission Information

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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. Actuators 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 2400 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

  • vibration control
  • adaptive control
  • predictive control
  • system identification
  • electric vehicles
  • automotive systems
  • robotic systems
  • vehicle suspension systems
  • power converters
  • electric motor actuators

Published Papers (2 papers)

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Research

20 pages, 524 KiB  
Article
Admissible Control for Non-Linear Singular Systems Subject to Time-Varying Delay and Actuator Saturation: An Interval Type-2 Fuzzy Approach
by Mourad Kchaou, Mohamed Amine Regaieg, Houssem Jerbi, Rabeh Abbassi, Dan Stefanoiu and Dumitru Popescu
Actuators 2023, 12(1), 30; https://doi.org/10.3390/act12010030 - 07 Jan 2023
Cited by 1 | Viewed by 1501
Abstract
Applied in many fields, nonlinear systems involving delay and algebraic equations are referred to as singular systems. These systems remain challenging due to saturation constraints that affect actuators and cause harm to their operation. Furthermore, the complexity of the problem will increase when [...] Read more.
Applied in many fields, nonlinear systems involving delay and algebraic equations are referred to as singular systems. These systems remain challenging due to saturation constraints that affect actuators and cause harm to their operation. Furthermore, the complexity of the problem will increase when uncertainty also simultaneously affects the system under consideration. To address this issue, this paper investigated a feasible control strategy for nonlinear singular systems with time-varying delay that are subject to uncertainty and actuator saturation. The IT-2 fuzzy model was adopted to describe the dynamic of the non-linear delayed systems using lower and upper membership functions to deal with the uncertainty. Moreover, the polyhedron model was applied to characterize the saturation function. The goal of the control approach was to design a relevant IT2 fuzzy state feedback controller with mismatched membership functions so that the closed-loop system is admissible. On the basis of an appropriate Lyapunov–Krasovskii functional, sufficient delay-dependent conditions were established and an optimization problem was formulated in terms of linear matrix inequality constraints to optimize the attraction domain. Simulation examples are provided to verify the effectiveness of the proposed method. Full article
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22 pages, 2117 KiB  
Article
Neural Adaptive Robust Motion-Tracking Control for Robotic Manipulator Systems
by Daniel Galvan-Perez, Hugo Yañez-Badillo, Francisco Beltran-Carbajal, Ivan Rivas-Cambero, Antonio Favela-Contreras and Ruben Tapia-Olvera
Actuators 2022, 11(9), 255; https://doi.org/10.3390/act11090255 - 07 Sep 2022
Cited by 5 | Viewed by 2119
Abstract
This paper deals with the motion trajectory tracking control problem based on output feedback and artificial neural networks for anthropomorphic manipulator robots under disturbed operating scenarios. This class of manipulator robots constitutes nonlinear dynamic systems subjected to disturbance torques induced mainly by work [...] Read more.
This paper deals with the motion trajectory tracking control problem based on output feedback and artificial neural networks for anthropomorphic manipulator robots under disturbed operating scenarios. This class of manipulator robots constitutes nonlinear dynamic systems subjected to disturbance torques induced mainly by work payload. Parametric uncertainty and possible dynamic modeling errors stand for other kind of disturbances that can deteriorate the efficiency and robustness of the tracking of controlled nonlinear robotic system trajectories. In fact, the presence of unknown dynamic disturbances is unavoidable in industrial robotic engineering systems. Therefore, for high-precision applications, such as laser cutting, marking, or welding, effective control schemes should be designed to guarantee adequate motion profile tracking planned on this class of disturbed nonlinear robotic system. In this context, a new adaptive robust motion trajectory tracking control scheme based on output feedback and artificial neural networks of anthropomorphic manipulator robots is presented. Three-layer B-spline artificial neural networks and time-series modeling are properly exploited in the design of novel adaptive robust motion tracking controllers for robotic applications of laser manufacturing. In this way, dependency on detailed nonlinear mathematical modeling of robotic systems is considerably reduced, and real-time estimation of uncertain dynamic disturbances is not required. Furthermore, several cases studies to demonstrate the motion planning tracking control robustness for a class of MIMO nonlinear robotic systems are described. blue Insights for the extension of the introduced output-feedback adaptive neural control design approach for other architecture of nonlinear robotic systems are depicted. Full article
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