This paper investigates the neural adaptive control problem for air-breathing hypersonic vehicles. For the velocity subsystem, a radial basis function neural network (RBFNN)-based adaptive controller is first designed, which employs the auxiliary variable to compensate for the saturation nonlinearity of the scramjet control command. For the altitude subsystem, an RBFNN-based controller addresses actuator constraints and dynamics using the model predictive control, as well as counteracts uncertainties and disturbances using the neural adaptive mechanism. The effectiveness of the proposed control is verified by simulations.

中文翻译：

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对执行器动力学鲁棒的吸气式高超声速飞行器的神经自适应控制

本文研究了吸气式高超音速飞行器的神经自适应控制问题。对于速度子系统，首先设计了基于径向基函数神经网络（RBFNN）的自适应控制器，该控制器采用辅助变量来补偿超燃冲压发动机控制指令的饱和非线性。对于高度子系统，基于 RBFNN 的控制器使用模型预测控制解决执行器约束和动力学问题，并使用神经自适应机制抵消不确定性和干扰。通过仿真验证了所提出的控制的有效性。