Tuaha Nomani

National University of Sciences and Technology

Papers

Total Citations

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About

Tuaha Nomani is a researcher specializing in intelligent control systems, artificial neural networks, and unmanned aerial vehicle (UAV) dynamics. His work focuses on applying bio-inspired computational models to real-world aerospace challenges, particularly the attitude stabilization of quadrotors. In his most cited paper, “Neural Network Controller for Attitude Control of Quadrotor” (2019), Nomani explores how artificial neural networks—inspired by the parallel processing and learning capabilities of the human brain—can replace traditional control algorithms for precise, adaptive flight control. This contribution addresses key limitations in conventional PID controllers, offering a robust alternative for autonomous UAV navigation. With 4 citations, the work has drawn interest from researchers in robotics, control theory, and neural computing. Nomani’s research sits at the intersection of artificial intelligence and aerospace engineering, demonstrating how ANN architectures can enhance function approximation and system response in dynamic environments. His insights into image association, recognition, and beam forming further extend the applicability of neural networks beyond control systems, marking him as a promising voice in the growing field of intelligent autonomous systems.