Iqbal Abiyoga
Papers
2
Total Citations
11
H-Index
2
About
Iqbal Abiyoga is a researcher focused on computational intelligence and autonomous robotics, with a specialization in neural network-based control systems. His primary research areas include backpropagation neural networks, direct inverse control schemes, and wheeled robot automation. Abiyoga’s major contributions center on developing optimal autonomous control systems for three-wheeled robots, where he pioneered the use of backpropagation-trained neural network controllers to enhance robot navigation and motor coordination. His most cited work, "Development of Computational Intelligence-based Control System using Backpropagation Neural Network for Wheeled Robot" (2018), has garnered 9 citations and established foundational methods for integrating neural networks into real-time robotic control. In subsequent research, "Improvement of Data Accuracy on Backpropagation Neural Network-based Automatic Control System for Wheeled Robot" (2020, 2 citations), he addressed critical challenges in training data precision, proposing strategies to reduce errors in direct inverse control frameworks. Though his citation counts are modest, Abiyoga’s work represents an important step toward more reliable, intelligent autonomous systems, particularly in educational and low-cost robotics contexts. His research bridges computational intelligence and practical engineering, offering accessible solutions for improving robot autonomy through neural network optimization.
Research Focus
Key Achievements
Top Papers
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