【摘 要】
：
针对飞控动态系统故障状态下安全飞行问题,提出了一种基于神经网络动态补偿的模型参考鲁棒容错控制方法.在经典RBF网络控制基础之上,设计了一种改进的神经网络结构,通过添加
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针对飞控动态系统故障状态下安全飞行问题,提出了一种基于神经网络动态补偿的模型参考鲁棒容错控制方法.在经典RBF网络控制基础之上,设计了一种改进的神经网络结构,通过添加直接输入输出线性环节,应用最近邻聚类和新的自适应C-均值聚类法训练改进后的神经网络,以及在线调整神经网络的权值和阙值,提高了网络的收敛速度和泛化能力,达到了飞控系统在线实时快速容错控制和抗干扰的目的.同时,证明了该闭环鲁棒容错控制算法的稳定性.在波音747-100/200模型上仿真实验表明了该方法的有效性和可行性.
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