A Varying-Parameter Convergent Neural Dynamic Controller of Multirotor UAVs for Tracking Time-Varying Tasks

作者：Zhang, Zhijun^*; Zheng, Lunan; Guo, Qi

来源：IEEE Transactions on Vehicular Technology, 2018, 67(6): 4793-4805.

DOI：10.1109/TVT.2018.2802909

• Unmanned aerial vehicle (UAV)
• neural dynamic method
• position and attitude angles
• tracking control

To stably control the position and attitude angles of an unmanned aerial vehicle (UAV), a varying-parameter convergent neural dynamic (VP-CND) method is proposed and applied. First, the dynamic models of multirotor UAVs are presented. Second, to meet the requirements of high accuracy and real-time control, a VP-CND method is proposed based on an error function to derive the position and attitude angle controllers. The existing fixed-parameter CND methods (e.g., the triple-Zhang dynamics or the Zhang dynamics and gradient dynamics) and the corresponding controllers are presented, and their limitations are analyzed. The proposed VP-CND control method not only can track time-varying target values but also possesses super-exponential convergence performance. Third, simulation comparisons verify the effectiveness, stability, and fast convergence of the VP-CND controllers.

• 出版日期2018-6
• 单位华南理工大学