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About

Andreja Rojko is a researcher whose work spans advanced motion control, robotics, and engineering education. Her primary contributions lie in the development of intelligent control strategies for robotic systems, particularly sliding-mode control enhanced with adaptive fuzzy and neural network techniques. Her most influential work, "Sliding-Mode Motion Controller With Adaptive Fuzzy Disturbance Estimation" (2004, 42 citations), introduced a novel adaptive fuzzy disturbance estimator capable of modeling complex robot dynamics, significantly improving control robustness in uncertain nonlinear environments. This research built upon her earlier investigations into fuzzy-based sliding mode control for direct drive robots and PI estimator-based disturbance rejection, forming a coherent body of work advancing high-performance robot motion control. Beyond control theory, Rojko has demonstrated a strong commitment to engineering education, exploring remote laboratory experiments for robot control teaching and championing lifelong learning in electromechanical industries — recognizing the critical need for practicing engineers to keep pace with rapid technological change. Her diverse contributions, spanning intelligent control algorithms, fuzzy load estimation, neural network applications in soccer robotics, and innovative pedagogical approaches, reflect a researcher equally invested in theoretical advancement and practical engineering education.