Ahmed Bilal Awan

National University of Sciences and Technology

Papers

Total Citations

H-Index

About

Ahmed Bilal Awan is a robotics researcher whose work focuses on the control of dynamically unstable, agile mobile platforms. His primary research area lies at the intersection of nonlinear control systems and intelligent optimization, specifically applying neural networks trained by particle swarm optimization (PSO) to complex robotic challenges. Awan's most cited work, "Control of a ball-bot using a PSO trained neural network" (2016, 2 citations), tackles the formidable problem of stabilizing and maneuvering a ball-bot—a robot that balances on a single spherical wheel. By modeling the ball-bot as two decoupled, 2-DOF pendulum-on-cart systems, he demonstrates a novel approach to high-speed control of inherently unstable platforms. This contribution is particularly valuable for advancing the agility and responsiveness of mobile robots in dynamic environments. While his citation count is modest, the work addresses a classical control problem with a modern, optimization-driven solution, showcasing Awan's ability to bridge theoretical control methods with practical robotic applications. His research offers a compelling foundation for students and engineers interested in intelligent control strategies for next-generation autonomous systems.