The nonlinear dynamic inversion controller based on online neural net is adopted for the attitude control loop.
基本姿态控制器采用基于在线神经网络的非线性动态逆控制器。
The design of the flight controller that exploits the advantages of the nonlinear dynamic inversion, adaptive fuzzy system and slide model control is discussed.
论述了综合运用非线性动态逆、自适应模糊系统和滑模控制的优点进行飞行控制律设计的方法。
On the basis of this model, the nonlinear dynamic inversion method was applied to design the pitch Angle controller of the system working above the rated wind speed.
在此基础上，利用非线性动态逆方法，设计了系统在额定风速以上工作时的桨距角控制律。
The base control law is designed in nonlinear dynamic inversion, and neural networks are used to cancel the inversion error induced by many reasons, especially by actuator failures.
飞机的基本控制律采用非线性动态逆方法设计，对于模型不准确和舵面故障等因素导致的逆误差采用神经网络进行在线补偿。
A discussion is devoted to the design of a self adaptive and nonlinear dynamic neural network inversion controller according to the feedback linearization theory.
根据反馈线性化理论，讨论了神经网络自适应非线性动态逆控制设计。
A plan of model reference adaptive tracking control for nonlinear systems is introduced based on neural network dynamic inversion (NNDI).
基于神经网络动态逆方法，给出了一种非线性模型参考自适应跟踪控制方案。
Two neural networks are used, the inversion of nonlinear systems is realized by off-line trained NN1, on-line NN2 is used to compensate inversion error and varieties of system dynamic property.
设计中使用了2个神经网络，经离线训练的NN1实现非线性系统的逆，在线网络NN2用于补偿逆误差和系统的动态特性变化。
The objective of this paper is to design the reentry flight control laws for the Suborbital Reusable Launch Vehicle(SRLV) based on nonlinear dynamic-inversion.
基于非线性动态逆理论，设计了亚轨道可重复使用运载器（SRLV）的再入控制律。
The objective of this paper is to design the reentry flight control laws for the Suborbital Reusable Launch Vehicle(SRLV) based on nonlinear dynamic-inversion.
基于非线性动态逆理论，设计了亚轨道可重复使用运载器（SRLV）的再入控制律。
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