%0 Journal Article
%T 基于ADRC姿态解耦的四旋翼飞行器鲁棒轨迹跟踪<br>Robust trajectory tracking for quadrotor aircraft based on ADRC attitude decoupling control
%A 杨立本
%A 章卫国
%A 黄得刚
%J 北京航空航天大学学报
%D 2015
%R 10.13700/j.bh.1001-5965.2014.0392
%X 摘要 针对欠驱动四旋翼飞行器的控制特性,提出一种基于自抗扰控制(ADRC)的姿态解耦控制算法,该算法可以克服传统欠驱动四旋翼控制方法中存在的问题,如系统状态间耦合严重,抗干扰能力弱及系统建模误差对跟踪性能影响较大等弱点.该算法利用扩张状态观测器(ESO)实现状态间耦合项的跟踪和估计,同时ESO也可实现对系统干扰的估计,干扰包括系统内扰和外扰.利用动态反馈线性化将非线性MIMO系统转化成线性SISO系统,然后利用非线性反馈控制律实现四旋翼姿态系统的高品质控制,在上述姿态解耦控制的基础上研究飞行器的鲁棒轨迹跟踪问题,不同情况下的仿真结果验证了上述姿态控制算法可提高系统轨迹跟踪的鲁棒性.该算法不依赖于精确的系统模型,降低了实际应用的难度,并有很强的抗干扰能力,具有实际应用的价值.<br>Abstract：An attitude decoupling algorithm based on active disturbance rejection control (ADRC) was designed for underactuated quadrotor aircraft. The algorithm can overcome some shortcomings of traditional control method for underactuated quadrotor, such as strong coupling between system states, weak anti-interference ability and high sensitivity of tracking performance to modeling errors, etc. The state coupling was tracked and estimated by extended state observer (ESO), system interference can be estimated by ESO at the same time. The interference of the system includes internal and external disturbances. The nonlinear multiple-input multiple-output (MIMO) system was transformed into linear single-input single-output (SISO) system by dynamic feedback linearization. Then using the nonlinear feedback control law to achieve high quality control of the attitude system, and study the robust trajectory tracking problem of the aircraft based on the attitude decoupling control algorithm. The simulation results show that the above attitude control algorithm can improve the robustness of the trajectory tracking system. The algorithm does not rely on the accurate system model, reduces the difficulty of practical application, and has strong anti-interference capability and practical application value as well.
%K 自抗扰控制
%K 四旋翼
%K 动态反馈线性化
%K 解耦
%K 粒子群优化
%K 干扰估计&lt
%K br&gt
%K active disturbance rejection controller
%K quadrotor
%K dynamic feedback linearization
%K decoupling
%K particle swarm optimization
%K interference estimation
%U http://bhxb.buaa.edu.cn/CN/abstract/abstract13285.shtml