Emil Y. Marinov

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About

Emil Y. Marinov is a researcher in the field of robotics and intelligent control systems, with a particular focus on neural network-based approaches for robotic manipulation. His work centers on the development of adaptive control strategies that leverage artificial neural networks to improve the autonomy and precision of robotic systems. Marinov’s most notable contribution is his pioneering study on the neural control of two-link planar robots, where he proposed a unified control architecture that integrates a feedforward neural network serving simultaneously as both a neural model and a neural controller. This innovative approach employs an on-line learning process based on gradient descent and error backpropagation, enabling the robot to adapt in real time to dynamic conditions. Although his seminal 2019 paper has garnered 5 citations, its conceptual elegance and practical relevance have established a foundation for further exploration in adaptive robotics. Marinov’s work is particularly valuable for students and researchers interested in bridging the gap between theoretical neural network learning and real-world robotic control applications.