applsci-logo

Journal Browser

Journal Browser

Motivation AI and Its Application to Smart Systems and Industrial Innovations

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 August 2025 | Viewed by 560

Special Issue Editor


E-Mail
Guest Editor
Department of Digital Electronics, Inha Technical College, 100 Inha-ro, Hagik 1(il)-dong, Nam-gu, Incheon, Republic of Korea
Interests: intelligent humanoid robot, autonomous multi-mobile robot system, and AI and its applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to bring together academics and industrial practitioners to exchange and discuss the latest innovations and applications of artificial intelligence (AI). In recent decades, automated and intelligent systems have emerged, opening new research directions that are still evolving due to new challenges and technological advances in the field.

Topics

The scope of this Special Issue encompasses the application of artificial intelligence techniques and algorithms to design and solve existing problems of smart systems. These techniques include the following:

  • Computer vision for smart systems;
  • Natural language interfaces for smart systems;
  • Knowledge-based smart systems;
  • Agent-based smart systems;
  • Fuzzy logic- or deep learning-based smart systems;
  • Artificial neural networks for smart systems;
  • Ontology-based smart systems;
  • Human–robot interaction for smart systems;
  • Smart systems in sensing and perception for robotic systems;
  • Bio-inspired and neural approaches to sensing, representation, and action for robotic systems;
  • Smart systems in machine vision for robotic systems.

Prof. Dr. Dong Won Kim
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. 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

  • intelligent modeling
  • application
  • control system
  • robotics system
  • knowledge-based system
  • artificial model forecasting

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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

Research

17 pages, 1086 KiB  
Article
Optimized Controller Design Using Hybrid Real-Time Model Identification with LSTM-Based Adaptive Control
by Yeon-Jeong Park and Joon-Ho Cho
Appl. Sci. 2025, 15(4), 2138; https://doi.org/10.3390/app15042138 - 18 Feb 2025
Viewed by 376
Abstract
Most of the processes with various dynamic characteristics can be reduced to the Second Order Plus Time Delay (SOPTD) model by using the model reduction method. We propose a novel hybrid approach that combines Long Short-Term Memory (LSTM)-based real-time model identification with Genetic [...] Read more.
Most of the processes with various dynamic characteristics can be reduced to the Second Order Plus Time Delay (SOPTD) model by using the model reduction method. We propose a novel hybrid approach that combines Long Short-Term Memory (LSTM)-based real-time model identification with Genetic Algorithms to enhance the Smith predictor control structure. This method compensates for the delay time of the SOPTD model while minimizing the Integral Time Absolute Error performance index. Our approach integrates an optimally adaptive Proportional–Integral–Derivative (PID) controller design algorithm that estimates the coefficients of the SOPTD model in the Smith Predictor control structure and adjusts the PID controller parameters dynamically. The method is improved through a combination of numerical calculation, Genetic Algorithms, and LSTM networks, showing approximately 15% better performance compared to conventional methods. The system demonstrates significant improvements in both performance metrics and resource utilization, including a 40% reduction in execution time and enhanced resource efficiency. Simulation results show that the proposed scheme exhibits improved adaptability to disturbances and process variations, with faster response times and reduced overshoots compared to traditional methods. The steady-state response of the higher-order model and the reduced model shows perfect matching for the unit feedback input. Full article
Show Figures

Figure 1

Back to TopTop