Walid Alqaisi

University of Doha for Science and Technology, Qatar Science and Technology Park

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About

Walid Alqaisi is a researcher specializing in nonlinear control systems, with a particular focus on robust and adaptive control strategies for robotic manipulators and unmanned aerial vehicles. His work addresses critical challenges in tracking control for uncertain dynamic systems, where parameter variations, unmodeled dynamics, and unknown perturbations degrade performance. Alqaisi’s most cited paper, "Modified Fast Terminal Super-Twisting Control for Uncertain Robot Manipulators" (2021, 5 citations), introduces an advanced sliding-mode approach that improves convergence speed and disturbance rejection, offering a model-free solution to complex robotic tracking problems. More recently, his 2024 paper on "Backstepping control based on neural network estimation" (2 citations) extends these ideas to quadrotor control, employing Radial Basis Function Neural Networks (RBFNN) to estimate and compensate for unknown disturbances and dynamic uncertainties. This work demonstrates a powerful synergy between backstepping control and neural network approximation, enhancing robustness in real-time applications. Alqaisi’s contributions are notable for bridging theoretical rigor with practical implementation, providing tools that enable safer and more precise operation of autonomous systems under real-world uncertainties. His research continues to influence the development of intelligent, adaptive controllers for next-generation robotics and aerospace platforms.