Papers
6
Total Citations
76
H-Index
4
About
Yuriy Zaporozhets is a robotics and intelligent control systems researcher whose work centers on the design and modeling of mobile robots capable of navigating challenging surfaces, including inclined and vertical ferromagnetic structures. His most significant contributions lie at the intersection of electromagnetic field theory, fuzzy logic, and neural network-based control, with a particular focus on developing reliable clamping force estimation methods for magnetically operated robotic movers. Zaporozhets is best known for pioneering neuro-fuzzy observer frameworks — specifically ANFIS-based hybrid computational systems — to identify and control clamping forces in magnetically driven mobile robots. His 2016 paper on this topic has garnered 28 citations, establishing it as a foundational reference in the field. Subsequent work further refined mathematical models using field theory methods, including secondary source techniques and integrated force calculations, providing robust tools for both permanent and electromagnet-based movers. Across his most-cited publications, Zaporozhets has accumulated over 75 citations, reflecting steady influence within the robotics and automation research community. His research offers practical value for industrial inspection robots operating on ferromagnetic infrastructure, such as pipelines, ship hulls, and steel structures, making his work highly relevant to both academic and applied engineering audiences.
Research Focus
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