Papers
30
Total Citations
348
H-Index
12
About
Yuriy Kondratenko is a prominent researcher whose work spans intelligent robotics, fuzzy control systems, machine learning, and automation — fields in which he has made sustained and influential contributions over four decades. His early foundational work, "Evolutionary adaptation of control processes in robots operating in nonstationary environments" (1983), established him as a pioneer in adaptive robotic control, a theme that continues to animate his research today. Kondratenko's most cited contribution, "Machine Learning Techniques for Increasing Efficiency of the Robot's Sensor and Control Information Processing" (2022, 40 citations), demonstrates his sustained relevance in applying cutting-edge AI methods to real-time industrial and robotic systems. His innovative development of neuro-fuzzy observers for clamping force estimation in mobile robots navigating ferromagnetic surfaces represents a particularly distinctive thread of inquiry, attracting significant scholarly attention across multiple publications. He has also advanced parametric optimization of fuzzy control systems using hybrid particle swarm algorithms, broadening the toolkit available to control engineers. As editor and co-author of widely referenced volumes on intelligent robotics and collaborative automation, Kondratenko has shaped the broader research community's direction. His work at Cleveland State University further highlights his international reach, bridging advanced modeling, prosthetics, and communication technologies in service of next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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- 4Advances in Intelligent Robotics and Collaborative Automation24 citations · 2015
- 5Slip displacement sensors for intelligent robots: Solutions and models22 citations · 2013
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