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Mechatronic Systems Design and Optimization
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Mechatronic Systems Design and Optimization

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 2254

Special Issue Editors

Dr. Stijn Derammelaere

E-Mail Website
Guest Editor
Department of Electromechanics, Faculty of Applied Engineering, Antwerp University, Groenenborgerlaan 171, B-2020 Antwerp, Belgium
Interests: motion planning and control; optimization; physical system modelling; electrical machines
Special Issues, Collections and Topics in MDPI journals
Dr. Amélie Chevalier

E-Mail Website
Guest Editor
Cosys-Lab Research Group, Department of Electromechanics, University of Antwerp, Antwerp, Belgium
Interests: controller design

Special Issue Information

Dear Colleagues,

Rapid advancements in robotics, automation, and mechatronics (RAM) are transforming industries, from manufacturing and healthcare to agriculture and service sectors. This Special Issue on Mechatronic Systems Design and Optimization highlights the cutting-edge research and emerging applications driving the evolution of intelligent systems.

We aim to explore breakthroughs that integrate advanced sensing, control, optimization and computational technologies to enhance efficiency, precision, and adaptability in design and operation of robotic and mechatronic systems. Topics of interest include but are not limited to the following:

  • Autonomous systems and robotics: Navigation, perception, and decision-making algorithms for autonomous vehicles, drones, and collaborative robots.
  • Human–robot interaction (HRI): Advances in intuitive interfaces, safety, and adaptive learning for seamless collaboration.
  • Mechatronic design innovations: Novel actuator and sensor technologies, soft robotics, and energy-efficient designs.
  • Automation in manufacturing and logistics: Smart factories, industrial IoT, and machine learning applications for predictive maintenance and quality control.
  • Medical robotics and assistive technologies: Surgical robotics, rehabilitation devices, and bio-inspired mechanisms.
  • Advanced control systems: AI-enhanced controllers, adaptive and nonlinear control strategies, and swarm robotics.
  • Emerging materials and fabrication methods: The role of 3D printing, flexible electronics, and new materials in robotic and mechatronic systems.

Design of robotic and mechatronic systems: Multi-disciplinary optimization, co-design of flexible robots, energy-efficient design optimization, topology optimization for robotic structures, geometric optimization for mechanism design, bio-inspired co-design, real-time optimization in adaptive systems, digital twins for design optimization, advanced simulation techniques, motion profile optimization, trajectory optimization, computationally efficient optimization, global optimization in mechatronics.

By fostering interdisciplinary dialogue, this Special Issue showcases transformative solutions and theoretical advancements that address real-world challenges. We encourage submissions that blend theoretical rigor with practical insights, highlighting novel methodologies, experimental validations, and applications with societal impact.

This collection aims to provide a comprehensive view of current trends and future directions, contributing to the growth of RAM as a cornerstone of technological progress.

Dr. Stijn Derammelaere
Dr. Amélie Chevalier
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 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. Applied Sciences 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 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

  • robotics
  • automation
  • mechatronics
  • manufacturing
  • healthcare
  • agriculture
  • sensing
  • control
  • computational technologies
  • optimization

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Published Papers (3 papers)

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Research

22 pages, 6206 KB  
Article
An Open-Source Software Framework for Direct Field-Oriented Control of a BLDC with Only One Sensor for ARM
by Radu Bogdan Sabau and Radu Etz
Appl. Sci. 2025, 15(20), 11018; https://doi.org/10.3390/app152011018 - 14 Oct 2025
Abstract
This paper introduces an open-source software framework for implementing Field-Oriented Control (FOC) on a Brushless DC Motor (BLDC) across its entire speed range. The control strategy employs a Direct FOC method with a single Hall sensor combined with Space Vector Pulse Width Modulation [...] Read more.
This paper introduces an open-source software framework for implementing Field-Oriented Control (FOC) on a Brushless DC Motor (BLDC) across its entire speed range. The control strategy employs a Direct FOC method with a single Hall sensor combined with Space Vector Pulse Width Modulation (SVPWM) and complementary sensorless techniques. The BLDC motor and supporting circuits are modeled and validated through both simulation and hardware implementation. A modular software architecture enables deployment via distinct system components, promoting hardware abstraction and reducing platform-specific dependencies. The entire setup is conceptualized and executed in MATLAB/Simulink R2024b and the framework supports remote experimentation through a web-based interface, requiring only a single MATLAB license. This scalable solution is designed for academic researchers and industry practitioners alike, offering an accessible low-cost platform for motor control development, validation, and early-stage prototyping. Full article
(This article belongs to the Special Issue Mechatronic Systems Design and Optimization)
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19 pages, 4057 KB  
Article
Multi-Objective Optimization of PMSM Servo System Control Performance Based on Artificial Neural Network and Genetic Algorithm
by Futeng Li, Xianglong Li, Huan Hou and Xiyang Xie
Appl. Sci. 2025, 15(18), 10280; https://doi.org/10.3390/app151810280 - 22 Sep 2025
Viewed by 391
Abstract
With the rapid advancement of intelligent technologies, permanent magnet synchronous motor (PMSM) servo systems have seen increasing applications in industrial fields, accompanied by continuously rising control performance demands. Moreover, the adjustment of controller parameters is pivotal for the performance optimization of servo systems. [...] Read more.
With the rapid advancement of intelligent technologies, permanent magnet synchronous motor (PMSM) servo systems have seen increasing applications in industrial fields, accompanied by continuously rising control performance demands. Moreover, the adjustment of controller parameters is pivotal for the performance optimization of servo systems. This paper presents an optimization method for PMSM servo systems based on the coupling technique of the neural network surrogate model and intelligent optimization algorithm. A hybrid model is constructed by the proposed method, integrating a mathematical model based on transfer functions with an artificial neural network surrogate model, which is employed to compensate for the discrepancies between the mathematical model and the actual measured values. The accuracy and superiority of the hybrid model are comprehensively validated through training and validation loss analysis, fitting plot construction, and ablation experiments. Subsequently, based on the hybrid model, the qualitative and quantitative comparative analysis of the Pareto fronts of five commonly used multi-objective intelligent optimization algorithms is conducted. The optimal algorithm is determined through experimental validation of the optimization results to obtain the optimal result. The optimal result demonstrates that, compared to the initial result before optimization, the overshoot is reduced by 89.7%, and the settling time is reduced by 80.1%. Additionally, several other non-dominated solutions are available for selection, and all optimized results are superior to the initial result. This study provides a novel idea and method for the performance optimization of PMSM servo systems, contributing to the field with a robust and effective approach to enhance system control performance. Full article
(This article belongs to the Special Issue Mechatronic Systems Design and Optimization)
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29 pages, 12889 KB  
Article
Development of a Multi-Robot System for Autonomous Inspection of Nuclear Waste Tank Pits
by Pengcheng Cao, Edward Kaleb Houck, Anthony D'Andrea, Robert Kinoshita, Kristan B. Egan, Porter J. Zohner and Yidong Xia
Appl. Sci. 2025, 15(17), 9307; https://doi.org/10.3390/app15179307 - 24 Aug 2025
Viewed by 1369
Abstract
This paper introduces the overall design plan, development timeline, and preliminary progress of the Autonomous Pit Exploration System project. This project aims to develop an advanced multi-robot system for the efficient inspection of nuclear waste-storage tank pits. The project is structured into three [...] Read more.
This paper introduces the overall design plan, development timeline, and preliminary progress of the Autonomous Pit Exploration System project. This project aims to develop an advanced multi-robot system for the efficient inspection of nuclear waste-storage tank pits. The project is structured into three phases: Phase 1 involves data collection and interface definition in collaboration with Hanford Site experts and university partners, focusing on tank riser geometry and hardware solutions. Phase 2 includes the selection of sensors and robot components, detailed mechanical design, and prototyping. Phase 3 integrates all components into a cohesive system managed by a master control package which also incorporates digital twin and surrogate models, and culminates in comprehensive testing and validation at a simulated tank pit at the Idaho National Laboratory. Additionally, the system’s communication design ensures coordinated operation through shared data, power, and control signals. For transportation and deployment, an electric vehicle (EV) is chosen to support the system for a full 10 h shift with better regulatory compliance for field deployment. A telescopic arm design is selected for its simple configuration and superior reach capability and controllability. Preliminary testing utilizes an educational robot to demonstrate the feasibility of splitting computational tasks between edge and cloud computers. Successful simultaneous localization and mapping (SLAM) tasks validate our distributed computing approach. More design considerations are also discussed, including radiation hardness assurance, SLAM performance, software transferability, and digital twinning strategies. Full article
(This article belongs to the Special Issue Mechatronic Systems Design and Optimization)
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