This research presents a comprehensive exploration of full-state feedback control design using optimal Linear Quadratic Regulator (LQR) techniques for achieving a smooth and stable descent during the landing phase of a drone. The study employs MATLAB Live Scripts, integrating interactive coding, data visualization, and documentation to facilitate a seamless design and simulation process. The primary focus lies in strategically placing poles to influence the system's dynamics, ensuring precise control over the drone's descent.

1. Introduction

The task of designing an effective control system for the smooth landing of a drone involves intricate considerations of dynamics, stability, and control strategies. This research addresses these challenges by employing full-state feedback control, utilizing optimal LQR techniques for enhanced performance.

2. Pole Placement Strategy

Pole placement plays a pivotal role in shaping the behavior of the control system. By strategically selecting five poles, we aim to achieve desired system dynamics and stability during the drone's descent. The careful placement of poles enables precise control over the system's response, ensuring a controlled and stable landing.

3. Optimal LQR Control

The study leverages the Linear Quadratic Regulator (LQR) framework, a powerful tool in control theory, to optimize the system's performance. The LQR controller is designed to minimize a cost function, incorporating both state and control inputs, thereby ensuring an optimal balance between control effort and system stability.

4. MATLAB Live Script Implementation

MATLAB Live Scripts are utilized to seamlessly integrate code, visualizations, and documentation. This approach enhances the accessibility and reproducibility of the control system design process. The interactive nature of Live Scripts allows for real-time adjustments, facilitating a dynamic exploration of different control strategies.

5. Experimental Results: Drone Control

The proposed control system is validated through extensive simulations, demonstrating the effectiveness of the pole placement strategy and optimal LQR control. The results showcase a smooth and stable descent of the drone, meeting the objectives of the landing task.

6. Conclusion

This research presents a robust approach to full-state feedback control design for drone landing, emphasizing the strategic use of pole placement and optimal LQR control. The integration of MATLAB Live Scripts enhances the transparency and reproducibility of the design process. The achieved results indicate the feasibility and effectiveness of the proposed control system.

7. Future Work

Future work could explore the application of advanced control techniques, real-time implementations, and adaptive strategies to further enhance the performance and robustness of the drone landing control system.

Affiliation

I would like to affiliate this project with Virginia Tech, which was performed under Dr. Steve Southward, Associate Professor.

Click to view the Source code

View the output simulation here