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Novel Fuzzy PID-Type Iterative Learning Control for Quadrotor UAV

機(jī)譯:四旋翼無人機(jī)的新型模糊PID型迭代學(xué)習(xí)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.
機(jī)譯:由于四旋翼飛行器驅(qū)動不足,耦合特性強,傳統(tǒng)的軌跡跟蹤方法控制精度低,抗干擾能力差。針對四旋翼無人機(jī)(UAV),設(shè)計了一種新型的模糊比例交互式導(dǎo)數(shù)(PID)型迭代學(xué)習(xí)控制(ILC)。該控制方法將PID-ILC控制和模糊控制相結(jié)合,從而繼承了ILC控制對干擾的魯棒性和系統(tǒng)模型的不確定性。提出了一種新的基于PID-ILC算法的控制律,以解決僅由ILC控制引起的外部干擾引起的抖振問題。使用模糊控制來設(shè)置三個學(xué)習(xí)增益矩陣的PID參數(shù),以抑制不確定因素對系統(tǒng)的影響并提高控制精度。使用Lyapunov穩(wěn)定性理論驗證了新設(shè)計的系統(tǒng)穩(wěn)定性。涼亭模擬表明,所提出的設(shè)計方法為四旋翼飛機(jī)創(chuàng)造了有效的ILC控制器。

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