An iterative LQR control method for 6-DOF UAV quadcopter under disturbance and payload variation
Abstract
This paper proposes an optimal control method based on the iterative LQR aimed at enhancing the trajectory tracking accuracy of a 6 DOF quadcopter UAV under external disturbances and varying payloads. The main distinguishing feature of the proposed method is the iterative optimization mechanism of the weighting matrices Q and R through the logarithmic normalization of error metrics, including ITAE, ISE, and RMSE, which automatically adjusts the controller based on the system's actual performance. The effectiveness of the method is evaluated through simulations in MATLAB across various flight trajectories and scenarios, including ideal conditions, disturbances, and combined disturbances with varying payloads. The simulation results show that the iterative LQR method significantly improves control quality compared to traditional PID and LQR controllers, with error reductions ranging from 6.6% to 41.8%, particularly evident in the x and y position axes and the yaw angle ψ. Furthermore, preliminary experimental results on quadcopter UAV hardware show that the proposed iterative LQR algorithm helps improve control quality and enhance flight attitude stability under low wind disturbance and varying payloads. These results demonstrate the adaptability and robustness of the proposed method under the complex operating conditions of UAVs.
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References
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