High Fidelity Quadcopter Dynamics
High Fidelity Quadcopter Dynamics
This collection of projects traces our journey in quadcopter control, aiming to make these unstable drones fly with precision and agility. We began by addressing the fundamental question: "How can we accurately model a quadcopter's complex, nonlinear dynamics?" This led to our first project, where we built a highly accurate digital model of a quadcopter, understanding its intricate physics.
Next, we tackled the crucial question: "Is it sufficient to design a controller based solely on a simplified linear model of a complex system, or must the full nonlinear dynamics be considered for real-world application?" In our second project, we attempted control with traditional methods like PID, but found it often responded slowly and required tedious adjustments. Our research revealed that while linear models are useful, the drone's actual nonlinear behavior demands more sophisticated control.
Finally, we culminated our work by answering: "How can we achieve highly responsive, precise, and constrained-aware control for a nonlinear quadcopter, effectively overcoming the practical challenges of classical methods?" For this, we developed an advanced Model Predictive Control (MPC) system. This smart controller predicts the drone's future, allowing it to plan optimal, smooth, and constrained-aware movements, dramatically enhancing responsiveness and overcoming the limitations of simpler approaches.
3. Nonlinear Model Predictive Control (NMPC) for Quadcopter