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Novel Fuzzy PID-Type Iterative Learning Control for Quadrotor UAV

机译:四旋翼无人机的新型模糊PID型迭代学习控制

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摘要

Due to the under-actuated and strong coupling characteristics of quadrotor aircraft, traditional trajectory tracking methods have low control precision, and poor anti-interference ability. A novel fuzzy proportional-interactive-derivative (PID)-type iterative learning control (ILC) was designed for a quadrotor unmanned aerial vehicle (UAV). The control method combined PID-ILC control and fuzzy control, so it inherited the robustness to disturbances and system model uncertainties of the ILC control. A new control law based on the PID-ILC algorithm was introduced to solve the problem of chattering caused by an external disturbance in the ILC control alone. Fuzzy control was used to set the PID parameters of three learning gain matrices to restrain the influence of uncertain factors on the system and improve the control precision. The system stability with the new design was verified using Lyapunov stability theory. The Gazebo simulation showed that the proposed design method creates effective ILC controllers for quadrotor aircraft.
机译:由于四旋翼飞行器驱动不足,耦合特性强,传统的轨迹跟踪方法控制精度低,抗干扰能力差。针对四旋翼无人机(UAV),设计了一种新型的模糊比例交互式导数(PID)型迭代学习控制(ILC)。该控制方法将PID-ILC控制和模糊控制相结合,从而继承了ILC控制对干扰的鲁棒性和系统模型的不确定性。提出了一种新的基于PID-ILC算法的控制律,以解决仅由ILC控制引起的外部干扰引起的抖振问题。使用模糊控制来设置三个学习增益矩阵的PID参数,以抑制不确定因素对系统的影响并提高控制精度。使用Lyapunov稳定性理论验证了新设计的系统稳定性。凉亭模拟表明,所提出的设计方法为四旋翼飞机创造了有效的ILC控制器。

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