Robust Control of Permanent Magnet Synchronous Motors (PMSM) and Induction Motors (IM)

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electrical Machines and Drives".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 2328

Special Issue Editor

Department of Industrial Technologies, Universidad de Santiago de Chile, Santiago, Chile
Interests: adaptive systems and electric machines control

Special Issue Information

Dear Colleagues,

As is well known, global electricity consumption has nearly doubled over the past twenty years. In this scenario, the robust control of permanent magnet synchronous motors (PMSM) and induction motors (IM) is essential to alleviate the global energy crisis since they consume half of the electrical energy produced in commercial, residential, and industrial applications. The PMSM has even moved towards replacing fossil fuel engines and creating new methods of transportation, which will soon be powered by renewable energy sources. On the other hand, after the progressive substitution of direct current (DC) motors over the last 30 years, the most efficient IMs (IE2, IE3, IE4) have recently evolved whilst also being able to maintain their lower cost and maintenance characteristics.

Based on these previous statements, Machines opened this Special Issue which covers the novel methods and technologies of the Robust Control of Permanent Magnet Synchronous Motors (PMSM) and Induction Motors (IM), and we invite you to contribute.

Proposals are expected to deal with the characteristics of these motors, their drives, and moved mechanisms, which have nonlinear behavior, uncertainties, and disturbances.

This Special Issue covers, but is not limited to, the following:

  • Nonlinear control, variable observers, and parameter estimators applied to the PMSM and IM, including their drivers and applications.
  • Monitoring and controlling these electrical machines for energy saving, operation supervision, maintenance planning, position tracking, and speed regulation.

All of these topics may consider different techniques, such as predictive control, H-infinite control, sliding mode control (SMC), passivity-based control, adaptive systems, predictive control, and artificial neural networks. 

Dr. Juan Carlos Travieso-Torres
Guest Editor

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. Machines 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.

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

18 pages, 1675 KiB  
Article
Simulation of the Circulating Bearing Currents for Different Stator Designs of Electric Traction Machines
by Yusa Tombul, Philipp Tillmann and Jakob Andert
Machines 2023, 11(8), 811; https://doi.org/10.3390/machines11080811 - 07 Aug 2023
Cited by 1 | Viewed by 960
Abstract
Pulse–width modulated inverters are commonly used to control electrical drives, generating a common mode voltage and current with high–frequency components that excite the parasitic capacitances within electric machines, such as permanent magnet synchronous machines or induction machines. This results in different types of [...] Read more.
Pulse–width modulated inverters are commonly used to control electrical drives, generating a common mode voltage and current with high–frequency components that excite the parasitic capacitances within electric machines, such as permanent magnet synchronous machines or induction machines. This results in different types of bearing currents that can shorten the service life of electric machines. One significant type of inverter–induced bearing currents are high–frequency circulating bearing currents. In this context, this work employs finite element analysis and time-domain simulations to determine the common mode current and circulating bearing current for various permanent magnet synchronous machine designs based on the traction machines of commercial electric vehicles with a focus on the stator. The results suggest that the ratio between the circulating bearing current and common mode current is much smaller in permanent magnet synchronous machines for traction applications than previously established in conventional induction machines, with values below 10% for all analyzed designs. A further increase in the robustness of such electric machines to the detrimental effects caused by the inverter supply could be achieved by reducing the parasitic winding–to–stator capacitance or by increasing the stator endwinding leakage inductance. Full article
Show Figures

Figure 1

14 pages, 4483 KiB  
Article
An Adaptive Torque Observer Based on Fuzzy Inference for Flexible Joint Application
by Yang Liu, Bao Song, Xiangdong Zhou, Yuting Gao and Tianhang Chen
Machines 2023, 11(8), 794; https://doi.org/10.3390/machines11080794 - 01 Aug 2023
Cited by 2 | Viewed by 650
Abstract
Torque observation techniques have been widely employed to estimate the load torque of flexible joints driven by a permanent magnet synchronous machine (PMSM). However, the performance of the observer degrades significantly when the position and orientation of the robot continuously changes, resulting in [...] Read more.
Torque observation techniques have been widely employed to estimate the load torque of flexible joints driven by a permanent magnet synchronous machine (PMSM). However, the performance of the observer degrades significantly when the position and orientation of the robot continuously changes, resulting in substantial irregular load variations. In this paper, an adaptive torque observer based on fuzzy inference is proposed to overcome this issue. Instead of relying on theoretical or numerical derivation, the relationship between the load inertia and the closed-loop poles of the torque observer is expressed by fuzzy inference. This approach enables the flexible configuration of the poles based on the load inertia, allowing for automatic tuning of the gain matrix. Consequently, the observer can ensure robustness and maintain superior performance under varying load conditions. The effectiveness of the proposed observer is validated through simulation and experimental results. It shows that compared to the classical Luenberger observer, the proposed adaptive torque observer can achieve more accurate observation results and exhibits a more dynamic response in the presence of varying load inertia. Full article
Show Figures

Figure 1

Back to TopTop