A Trajectory Tracking Method Using Convex Optimization
Ze An, Fenfen Xiong, Chao Li · 2020
To improve the efficiency of the existing convex optimization-based trajectory tracking method, and address the issue that the existing trajectory tracking methods are very sensitive to the deviations of axial states, a new trajectory tracking method using convex optimization in conjunction with a modified receding horizon control strategy is developed in this paper. The trajectory tracking is implemented in each segment of trajectory in successive using the convex optimization method. To ensure online guidance, the optimal control problem of trajectory tracking in each segment is transformed into an exact convex optimization, which can be solved in only one iteration. Meanwhile, to address the deviation of axial states, a time re-planning method is proposed to ensure the accuracy and robustness of trajectory tracking. Simulation results show that the proposed methods can track the reference trajectory with high accuracy and robustness with respect to various disturbances.