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Neuro-based adaptive controller for longitudinal flight control

机译:用于纵向飞行控制的基于神经的自适应控制器

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This paper provides some detailed analysis of the stability of the proposed direct adaptive controller for a special type of nonlinear system based on the previously published papers. The special learning algorithm similar to back propagation provides better stability and wide domain of attraction for the controller provided that the neural network parameters are chosen carefully. The controller acts as a direct adaptive controller and the weight and bias matrices are updated online without any prior offline training. It is easy to implement in real time due to less complexity in terms of absence of several neural networks. In this paper, we will be analyzing the Lyapunov stability of the neuro-based adaptive controller and show the simulation result on a F-8 aircraft control system model.
机译:本文根据以前发表的论文,对提出的用于特殊类型非线性系统的直接自适应控制器的稳定性进行了详细分析。如果仔细选择神经网络参数,类似于反向传播的特殊学习算法可为控制器提供更好的稳定性和更广的吸引力。该控制器充当直接自适应控制器,并且无需事先进行任何离线培训即可在线更新权重和偏差矩阵。由于缺少几个神经网络,因此复杂度较低,因此实时性很容易实现。在本文中,我们将分析基于神经的自适应控制器的Lyapunov稳定性,并在F-8飞机控制系统模型上显示仿真结果。

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