Feedback Linearization

Feedback linearization is a nonlinear control technique aiming to simplify complex system dynamics by transforming them into a linear form, enabling the application of simpler linear control methods. Current research focuses on extending its applicability to systems with inherent complexities like zero dynamics, model uncertainties, and singular input matrices, often employing data-driven approaches such as local model networks or physics-informed machine learning to address these challenges. This methodology finds significant application in diverse fields, including robotics (manipulators, UAVs, and even complex systems like quadrotors with pendulums), improving trajectory tracking precision and robustness while handling model inaccuracies and external disturbances.