Papers
14
Total Citations
73
H-Index
4
About
Ali Jebelli is a robotics and intelligent systems researcher whose work spans autonomous underwater vehicles (AUVs), quadrotor fault tolerance, and smart manufacturing. His most impactful contribution, an intelligent manufacturing approach using deep learning for automatic machine and working status recognition, has garnered 16 citations and addresses critical inspection needs in Industry 4.0. Jebelli has also advanced thermal management for mobile robots in extreme environments through fuzzy logic control, earning 14 citations. His foundational work on fault-tolerant control for micro quadrotors—using feedback linearization to maintain flight despite rotor loss—has been cited 7 times and demonstrates his focus on safety-critical systems. Jebelli’s sustained interest in underwater robotics is evident across multiple papers, including the design and implementation of a PTFE-based AUV (6 citations), modeling of rotating thruster vehicles (4 citations), and intelligent magnetic field methods to increase operating depth (4 citations). His early work on fuzzy logic PID control for energy-efficient underwater robots (3 citations) laid the groundwork for later innovations. With a portfolio that integrates deep learning, fuzzy logic, and robust control, Jebelli’s research directly impacts autonomous systems in manufacturing, aerospace, and marine exploration.
Research Focus
Key Achievements
Top Papers
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- 3Feedback linearization approach to fault tolerance for a micro quadrotor7 citations · 2018
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- 5Modeling of an Autonomous Underwater Robot with Rotating Thrusters4 citations · 2017
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- 9Design and Control of Underwater Robots with Rotating Thrusters3 citations · 2016
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