Intelligent Mechatronics System Modeling, Control and Evaluation

Topic Information

Dear Colleagues,

With the continuous development of artificial intelligence technology, mechatronics equipment represented by intelligent vehicles, engineering machinery, robots, and unmanned systems have played an increasingly important role. This mechatronic equipment has significantly improved operational accuracy, efficiency, and safety in hazardous environments by integrating artificial intelligence, and can achieve autonomous and collaborative capabilities beyond human capabilities. However, they also commonly face challenges such as technological reliability (especially in complex scenarios), high costs, and network security. Looking ahead to the future, we should focus on developing research directions such as embodied intelligence and autonomous decision-making (enabling equipment to truly understand the physical world and adapt to it), multi-machine collaboration and cluster intelligence (achieving efficient collaboration of large-scale equipment), human–machine integration and safe interaction (ensuring natural and safe collaboration between humans and systems), and synchronously construct corresponding testing standards, safety regulations, and ethical frameworks to promote their advancement towards higher levels of intelligence and scale applications, thereby better serving social and economic development.

Potential topics include, but are not limited to, the following:

• Design of intelligent mechatronics systems;
• New technologies of intelligent mechatronics systems;
• Thermal and energy management of intelligent mechatronics systems;
• Analysis, control, and testing of intelligent mechatronics systems;
• Case studies of successful intelligent mechatronics systems.

Prof. Dr. HongYu Zheng
Dr. Yong Li
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Machines machines	2.5	4.7	2013	17.6 Days	CHF 2400	Submit
Actuators actuators	2.3	4.3	2012	20.9 Days	CHF 2400	Submit
Applied Sciences applsci	2.5	5.5	2011	16 Days	CHF 2400	Submit

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (1 paper)

Order results

Content type Publication Date

Result details

Normal Extended Compact

Journals

All Machines Actuators Applied Sciences

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

Error

Oops... you haven't selected anything for export.

Ok

clear

26 pages, 5612 KB  

Open AccessArticle

Dynamics Parameter Calibration for Performance Enhancement of Heavy-Duty Servo Press

by Jian Li, Shuaiyi Ma, Bingqing Liu, Tao Liu and Zhen Wang

Appl. Sci. 2026, 16(2), 847; https://doi.org/10.3390/app16020847 - 14 Jan 2026

Viewed by 68

Abstract

The accuracy of dynamics parameters in the transmission system is essential for high-performance motion trajectory planning and stable operation of heavy-duty servo presses. To mitigate the performance degradation and potential overload risks caused by deviations between theoretical and actual parameters, this paper proposes [...] Read more.

The accuracy of dynamics parameters in the transmission system is essential for high-performance motion trajectory planning and stable operation of heavy-duty servo presses. To mitigate the performance degradation and potential overload risks caused by deviations between theoretical and actual parameters, this paper proposes a dynamics model accuracy enhancement method that integrates multi-objective global sensitivity analysis and ant colony optimization-based calibration. First, a nonlinear dynamics model of the eight-bar mechanism was constructed based on Lagrange’s equations, which systematically incorporates generalized external force models consistent with actual production, including gravity, friction, balance force, and stamping process load. Subsequently, six key sensitive parameters were identified from 28 system parameters using Sobol global sensitivity analysis, with response functions defined for torque prediction accuracy, transient overload risk, thermal load, and work done. Based on the sensitivity results, a parameter calibration model was formulated to minimize torque prediction error and transient overload risk, and solved by the ant colony algorithm. Experimental validation showed that, after calibration, the root mean square error between predicted and measured torque decreased significantly from 1366.9 N·m to 277.7 N·m (a reduction of 79.7%), the peak error dropped by 72.7%, and the servo motor’s effective torque prediction error was reduced from 7.6% to 1.4%. In an automotive door panel stamping application on a 25,000 kN heavy-duty servo press, the production rate increased from 11.4 to 11.6 strokes per minute, demonstrating enhanced performance without operational safety. This study provides a theoretical foundation and an effective engineering solution for high-precision modeling and performance optimization of heavy-duty servo presses. Full article

(This article belongs to the Topic Intelligent Mechatronics System Modeling, Control and Evaluation)

►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

 

Error

Oops... you haven't selected anything for export.

Ok

clear

Displaying articles 1-1