Dong LT Tran | Searcharxiv

arXiv2025

Design Optimal Backstepping Controller for Quadrotor Based on Lyapunov Theory for Disturbances Environments

Various control methods have been studied to control the position and attitude of quadrotors. There are some differences in the mathematical equations between the two types of quadrotor configurations that lead to different control efficiency in disturbance environments. This paper described the nonlinear back stepping approach based on the Lyapunov function theory and LaSalle Principle for the quadrotor control system, which can provide the stability of all system states during the tracking of the desired trajectory. Accordingly, a mathematical model of the cross quadrotor configuration together with the controller has been built to stabilize the altitude and position of the quadrotor. To clarify the effectiveness of this method with the selected quadrotor configuration, we compare it with a traditional PID controller in an environment affected by disturbances. The simulation results in MATLAB show satisfactory stability of the quadrotor flight and following certain trajectories, confirming the accuracy and validity of the control method.

eess.SY↗

arXiv2024

Model Predictive Control for Optimal Motion Planning of Unmanned Aerial Vehicles

Motion planning is an essential process for the navigation of unmanned aerial vehicles (UAVs) where they need to adapt to obstacles and different structures of their operating environment to reach the goal. This paper presents an optimal motion planner for UAVs operating in unknown complex environments. The motion planner receives point cloud data from a local range sensor and then converts it into a voxel grid representing the surrounding environment. A local trajectory guiding the UAV to the goal is then generated based on the voxel grid. This trajectory is further optimized using model predictive control (MPC) to enhance the safety, speed, and smoothness of UAV operation. The optimization is carried out via the definition of several cost functions and constraints, taking into account the UAV's dynamics and requirements. A number of simulations and comparisons with a state-of-the-art method have been conducted in a complex environment with many obstacles to evaluate the performance of our method. The results show that our method provides not only shorter and smoother trajectories but also faster and more stable speed profiles. It is also energy efficient making it suitable for various UAV applications.

cs.RO↗