• This paper presents a dynamic inversion control method for high Angle - of - attack flight.

    提出了一种飞机大仰角飞行的动态逆模糊集成控制方法。

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  • 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。

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  • The base control law is designed in dynamic inversion and neural networks are used to reconstruct inversion error.

    基本控制律采用非线性动态逆方法设计,神经网络用于对逆误差进行重构。

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  • Design of a unmanned helicopter command controller using combination of dynamic inversion and a on line neural network is presented.

    使用动态逆和在线神经网络相结合的方法设计了无人直升机的指令控制器。

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  • 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。

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  • The networks are trained by the fast BP algorithm via fuzzy variables decision, and training samples are provided by the dynamic inversion control results.

    网络的训练利用改进的BP算法,将因子模糊化快速进行。样本点数据则由利用动态逆控制所得到的结果来提供。

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  • 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。

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  • 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。

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  • According to the singularity perturbation theory, dynamic inversion is adopted to design the basic attitude controller including fast inverse loop and slow inverse loop.

    利用多重时间尺度奇异摄动理论,结合非线性动态逆方法设计了基本姿态控制器,包括快逆回路和慢逆回路两部分。

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  • According to the characters of Dynamic Inversion method in making multivariable control system decoupling, we design a set of control law for every direct lift control mode.

    本文针对动态逆控制方法的不足之处提出了相应的改善措施,并取得了较为理想的效果。

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  • The dynamic inversion controller is used to eliminate the nonlinearity and the online neural net is used to compensate the state error caused by the elimination imprecision.

    动态逆控制器用来对消无人机的非线性,在线神经网络补偿对消不精确引起的状态误差。

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  • 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。

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  • Learn about additional techniques, such as adding manageability and inversion of control, to provide complex and dynamic component relationships, helping both users and system administrators.

    了解一些附加的技术,如添加可管理性和反向控制,以便提供复杂的和动态的组件关系,从而为用户和系统管理员提供帮助。

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  • This paper presents the analysis of the vertical viscoelastic dynamic responses of pipe group by Laplace numerical inversion method.

    应用担普拉斯数值反演方法分析了群桩垂向粘弹性动力反应。

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  • 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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  • 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。

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  • In this paper, the dynamic mechanical property and the phase inversion of the polyurethane (PU) -polyvinyl (PVA) blend system were studied.

    本文研究了聚氨酯(PU) -聚乙烯醇(PVA)共混体系的动态力学性质、相逆转现象和透气性能。

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  • Objective To characterize the dynamic contrast enhancement in focal hepatic lesions with pulse inversion harmonic (PIH) ultrasonographic imaging.

    目的探讨不同肝局灶性病变在超声造影反向脉冲谐波显像时的动态灌注过程及其特征。

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  • 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。

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  • 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。

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