基于滑模控制的传感器故障无人机主动容错控制

Wasif Shabbir, Li Aijun, M. Taimoor, Cui Yuwei, Muhammad Auwal Shehu
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引用次数: 0

摘要

本文采用滑模控制方法解决了存在螺距速率陀螺仪故障的无人机俯仰跟踪控制问题。采用高增益观测器(HGO)和径向基函数神经网络(RBFNN)两种不同的观测器进行故障估计。在控制律中采用实时故障估计来抵消故障的影响。在控制的开关部分采用功率趋近律解决了SMC的抖振问题。这形成了一个主动的容错控制,而不需要重新配置控制器。利用李雅普诺夫方法证明了故障系统的稳定性。将该方法应用于雅克-54型无人机的俯仰跟踪控制。仿真结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Active Fault Tolerant Control for a UAV Subject to Sensor Faults Using Sliding Mode Control
Unmanned aerial vehicle (UAV) pitch tracking control in the presence of pitch rate gyro sensor faults is addressed in this work using sliding mode control (SMC). Fault estimation is carried out using two different observers, a high gain observer (HGO) and a radial basis function neural network (RBFNN). Real-time fault estimations are used in the control law to counter the effects of the faults. The chattering problem of SMC is resolved using a power reaching law in the switching part of the control. This forms an active fault tolerant control without the need for controller reconfiguration. The stability of the faulty system is proved using the Lyapunov method. The proposed strategy is applied to pitch tracking control of a scaled Yak-54 UAV. The simulation results show the effectiveness of the proposed methodology.
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