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Robust Control of Electric Drives and Mechatronic Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (28 November 2024) | Viewed by 1899

Special Issue Editor


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Guest Editor
Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK
Interests: intelligent nonlinear control system design; intelligent optimization methods; intelligent nonlinear control system; sliding mode control; adaptive controller design; fuzzy systems; model predictive control
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Special Issue Information

Dear Colleagues,

Electric devices are the building blocks for mechatronics systems in general. As such, they must be able to deal with the uncertainties caused by simplified models, disturbances, parameter variations, and unmodeled dynamics. Robust control approaches benefit from the use of mechanisms to stabilize and maintain the performance in the presence of such uncertainties. Robust control approaches are capable of controlling electric motors and actuators including induction motors, brushless DC motors, and servo systems for use in mechatronic challenges and robotic tasks within an industrial environment. Energy efficiency, sustainability, and control performance, including speed and tracking performance, are among the most important control targets.

Motivated by the aforementioned challenges, this Special Issue of Energies will publish original research papers devoted to techniques, methods, applications, and industrial case studies reporting linear and nonlinear robust control approaches for electric drives and mechatronic systems. Energy-focused applications including in energy carriers, end-user energy consumption, energy conversion systems, and energy research and development are especially welcome for inclusion in this Special Issue. This Special Issue aims to serve as a means to present and share state-of-the-art approaches and up-to-date techniques in the robust control of electric drives, and mechatronics systems.

Dr. Mojtaba Ahmadieh Khanesar
Guest Editor

Manuscript Submission Information

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Keywords

  • robust control of electric drives and mechatronics systems
  • micro- and nano-electric drives and mechatronics systems
  • observer-based robust control of mechatronics systems
  • robotic applications
  • power electronic for electric drives
  • robust control within Industry 4.0 framework

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Published Papers (1 paper)

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Research

17 pages, 4519 KiB  
Article
Interval Type-2 Fuzzy Logic Control of Linear Stages in Feedback-Error-Learning Structure Using Laser Interferometer
by Mojtaba A. Khanesar, Minrui Yan, Aslihan Karaca, Mohammed Isa, Samanta Piano and David Branson
Energies 2024, 17(14), 3434; https://doi.org/10.3390/en17143434 - 12 Jul 2024
Cited by 1 | Viewed by 1102
Abstract
The output processer of interval type-2 fuzzy logic systems (IT2FLSs) is a complex operator which performs type-reduction plus defuzzification (TR+D) tasks. In this paper, a complexity-reduced yet high-performance TR+D for IT2FLSs based on Maclaurin series approximation is utilized within a feedback-error-learning (FEL) control [...] Read more.
The output processer of interval type-2 fuzzy logic systems (IT2FLSs) is a complex operator which performs type-reduction plus defuzzification (TR+D) tasks. In this paper, a complexity-reduced yet high-performance TR+D for IT2FLSs based on Maclaurin series approximation is utilized within a feedback-error-learning (FEL) control structure for controlling linear move stages. IT2FLSs are widely used for control purposes, as they provide extra degrees of freedom to increase control accuracies. FEL benefits from a classical controller, which is responsible for providing overall system stability, as well as a guideline for the training mechanism for IT2FLSs. The Kalman filter approach is utilized to tune IT2FLS parameters in this FEL structure. The proposed control method is applied to a linear stage in real time. Using an identification process, a model of the real-time linear stage is developed. Simulation results indicate that the proposed FEL approach using the Kalman filter as an estimator is an effective approach that outperforms the gradient descent-based FEL method and the proportional derivative (PD) classical controller. Motivated by the performance of the proposed Kalman filter-based FEL approach, it is used to control a linear move stage in real time. The position feedback of the move stage is provided by a precision laser interferometer capable of performing measurements with an accuracy of less than 1 μm. Using this measurement system in a feedback loop with the proposed control algorithm, the overall steady state of the system is less than 20 μm. The results illustrate the high-precision control capability of the proposed controller in real-time. Full article
(This article belongs to the Special Issue Robust Control of Electric Drives and Mechatronic Systems)
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