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Novel Sensing Methods in Advanced Manufacturing Systems
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Novel Sensing Methods in Advanced Manufacturing Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Industrial Sensors".

Deadline for manuscript submissions: 20 December 2026 | Viewed by 814

Editors

Dr. Meysam Zareiee

E-Mail Website
Guest Editor
School of Computer Science and Engineering, The University of Sunderland, Sunderland, UK
Interests: industrial automation; discrete event and manufacturing systems; supervisory control theory; the modeling of semiconductor devices
Dr. Mahsa Mehrad

E-Mail Website
Guest Editor
School of Electrical and Mechanical Engineering, University of Portsmouth, Portsmouth, UK
Interests: semiconductor devices; power electronic transistors; circuit design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of advanced manufacturing demands innovative sensing solutions that can enhance precision, efficiency, and adaptability in modern production environments. As manufacturing systems transition toward Industry 4.0 and 5.0 paradigms, sensors play an increasingly pivotal role in enabling cyber–physical systems, digital twins, and predictive maintenance frameworks. This Special Issue focuses on novel sensing methods and smart sensor integration in advanced manufacturing systems, including both hardware innovations and intelligent data-driven approaches. Topics of interest include developments in sensor design, data acquisition, signal processing, and the application of artificial intelligence for real-time monitoring, fault detection, and process optimization.

We welcome original research and comprehensive reviews that explore emerging sensing techniques, multi-sensor fusion, industrial IoT implementations, and sustainable sensing technologies for automated and adaptive manufacturing.

By addressing current challenges and presenting forward-looking perspectives, this collection aims to advance the understanding and application of sensing technologies that empower the next generation of intelligent manufacturing systems.

Dr. Meysam Zareiee
Dr. Mahsa Mehrad
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly 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 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

  • advanced manufacturing
  • smart sensors
  • Industry 4.0 and 5.0
  • sensor fusion
  • cyber–physical systems
  • digital twins
  • predictive maintenance
  • intelligent sensing
  • industrial IoT
  • process monitoring

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Published Papers (1 paper)

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Research

22 pages, 7796 KB  
Article
Sensorless Speed Control of PMSMs Based on an Improved Fast Power Reaching Law
by En Lu, Yufei Liu, Minghui Zhang and Jinyong Ju
Sensors 2026, 26(12), 3737; https://doi.org/10.3390/s26123737 - 11 Jun 2026
Viewed by 421
Abstract
Traditional permanent magnet synchronous motor (PMSM) control systems rely on mechanical position sensors for high-precision rotor position and speed information, which increases hardware complexity, raises system cost, reduces reliability, and limits adaptability to harsh environments. To overcome the above limitations, this paper proposes [...] Read more.
Traditional permanent magnet synchronous motor (PMSM) control systems rely on mechanical position sensors for high-precision rotor position and speed information, which increases hardware complexity, raises system cost, reduces reliability, and limits adaptability to harsh environments. To overcome the above limitations, this paper proposes a novel high-performance sensorless speed control strategy for PMSMs, which is constructed based on a non-singular terminal sliding mode observer (NTSMO) and a non-singular terminal sliding mode controller (NTSMC). First, an improved fast power reaching law (IFPRL) is proposed, which consists of a variable exponential reaching term and a power reaching term. Specifically, the gain of the exponential reaching term is dynamically adjusted by the absolute value of the sliding mode switching function, enabling the reaching law to operate in two different modes throughout the entire convergence process of the system state. Moreover, the introduction of scaling coefficient c compensates for the performance degradation caused by variations in the range of sliding mode surfaces (SMSs) in different systems. The proposed IFPRL not only effectively mitigates the inherent chattering issue, it also expedites the rate at which the system state converges to its SMS. On this basis, both the NTSMO for rotor position observation and the NTSMC for speed closed-loop control are designed by embedding the proposed IFPRL into the framework of non-singular terminal sliding mode control theory. Finally, the effectiveness of the proposed method is validated through numerical simulations and experimental tests. Experimental results demonstrate that the proposed IFPRL-based NTSMC + NTSMO scheme reduces the root mean square error (RMSE) of speed control by 2.7% relative to the traditional SMC + SMO method. The proposed method realizes reliable sensorless speed control for PMSMs and exhibits superior dynamic response, higher control accuracy, and stronger robustness against disturbances. Full article
(This article belongs to the Special Issue Novel Sensing Methods in Advanced Manufacturing Systems)
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