Special Issues
Table of Content

Intelligent Control and Sensing for Industrial and Autonomous Applications

Submission Deadline: 30 September 2026 View: 78 Submit to Special Issue

Guest Editors

Assoc. Prof. Nur Syazreen Ahmad

Email: syazreen@usm.my

Affiliation: School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

Homepage:

Research Interests: intelligent control and sensing, intelligent optimization, autonomous systems, sensor networks

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Assist. Prof. Mohd Fitri Mohd Yakub

Email: mfitri.kl@utm.my

Affiliation: Malaysia- Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

Homepage:

Research Interests: intelligent control, automatic and robust control, motion control, vehicle dynamics system, IoT, machine learning application

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Dr. Andika Aji Wijaya

Email: andika@ubt.edu.sa

Affiliation: Department of Mechanical Engineering, University of Business and Technology, Jeddah, Saudi Arabia

Homepage:

Research Interests: nonlinear control, vibration control, intelligent systems

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Summary

Introduction
Intelligent control and sensing play a critical role in the advancement of industrial and autonomous systems, allowing machines to perceive their environment, learn from data, and respond adaptively. Their integration supports improved performance, safety, and operational reliability in demanding real-world scenarios.


Aim and Scope
This Special Issue aims to showcase recent advances in intelligent control and sensing for industrial and autonomous applications. Topics of interest include data-driven modeling, machine learning-based sensing, optimal, adaptive, and robust control strategies, sensor fusion, and metaheuristic optimization algorithms that support decision-making and controller tuning. Contributions involving theoretical methods, computational tools, embedded implementations, and real-world case studies are welcome. Relevant application domains include robotics, industrial automation, transportation, and smart manufacturing, with emphasis on interdisciplinary research that bridges control, sensing, optimization, and practical deployment challenges.


Themes
· Machine learning and data-driven methods for sensing and control
· Optimal, adaptive, and robust control strategies
· Metaheuristic and evolutionary optimization algorithms for tuning and decision-making
· Sensor fusion, perception, and state estimation in autonomous systems
· Industrial automation, smart manufacturing, and process control
· Embedded sensing, real-time computing, and hardware-in-the-loop validation
· Applications in robotics, transportation, logistics, and infrastructure inspection


Graphic Abstract

Intelligent Control and Sensing for Industrial and Autonomous Applications

Keywords

intelligent control, intelligent sensing, metaheuristic optimization, machine learning, sensor fusion, state estimation, robotics and autonomous systems, industrial automation, smart manufacturing, data-driven modeling

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