Hamza Abdinassir Hassan

Developing and maintaining embedded systems software in C++ for robotic training systems, including hardware interfacing, sensor integration, and control algorithms.

Member of the Aalborg University team competing in the international European Rover Challenge (ERC), participating in the ERC 2024 finals in Krakow, Poland.

Working mainly with predictive maintenance for centrifugal pumps using deep learning and classical machine learning.

Internship working with non-linear model predictive controller for trailer-mobile robot system.

Master thesis abstract: This thesis addresses the problem of controlling a fleet of agents subject to disturbances and input/state constraints, with a focus on ensuring robustness to these disturbances. The control problem is defined for a set of agents operating in a shared workspace, where each agent must follow a desired trajectory while avoiding collisions and maintaining network connectivity. A decentralized tube based Nonlinear Model Predictive Control is developed (NMPC) to meet these objectives with an analytically derived control policy based on a Lyapunov candidate function to define the tube. Experimental results demonstrate that the NMPC approach effectively follows desired trajectories and mitigates disturbances. The leader and follower agents maintain low distance and orientation errors. The control strategy successfully avoids obstacles, prevents inter-agent collisions, and maintains communication constraints.