Jozef Peterka

Slovak University of Technology in Bratislava

Papers

Total Citations

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About

Jozef Peterka is a leading researcher in the diagnostics and control of electric drives for industrial robotics and CNC machine tools. His work focuses on integrating artificial intelligence and sensor support to enhance the reliability and precision of automated systems. Peterka’s most influential contribution is the development of a logical-linguistic model for diagnosing electric drives, which employs fuzzy inference rules to identify faults in robot actuators. This AI-driven approach, detailed in his 2020 paper (29 citations), represents a significant step toward self-diagnosing industrial machinery. He has further advanced the field by applying state-space identifiability criteria to diagnose actuators in machine tool drives, addressing the critical challenge of controlling non-linear systems where traditional linear models fail. His 2021 paper (7 citations) tackles this practical limitation, proposing algorithms that work in real-world, non-linear conditions. Peterka’s work is highly relevant to the ongoing push for smarter, more autonomous manufacturing, where predictive maintenance and fault detection are essential for minimizing downtime. His research bridges theoretical control engineering with practical, sensor-rich applications, making him a key figure in the evolution of intelligent industrial drives.