Finally, three forms of agility maneuvers arerealized by three nonlinear decoupling control forms of aircraft motion and the results aresatisfying.
最后用飞机非线性运动的三种解耦运动模式实现了三种形式的敏捷性机动，结果是满意的。
A decoupling control approach based on inverse system has been used for the innovative five degree-of-freedom bearing less induction motor, which is multi-variable, nonlinear and high coupling.
针对新型五自由度无轴承异步电动机这一多变量、非线性、强耦合的系统，采用逆系统的方法进行解耦控制。
After the success in decoupling, single neural cell self-adapting PID is adopted to control nonlinear object. The simulation results show that the control strategy gets better effects.
当解耦器训练结束后，对于非线性对象采用单神经元自适应PID来进行控制，仿真结果表明，此控制方案效果较好。
Flight control system designed by this nonlinear control method can achieve decoupling control, and has better adaptability to inaccurateness of model and the change of system parameters.
用该非线性控制方法设计的飞行控制系统不仅能够实现动态解耦控制，获得良好的动态性能，而且对模型不够准确或系统内部参数发生变化具有较强的适应性。
For nonlinear attitude system of flying vehicle with pure time-delay, inertia and bang-bang control a control method using decoupling variable structure is given.
对于具有纯延迟、惯性和由开关控制的非线性飞行器姿态系统，本文提出了采用解耦变结构控制的方法。
A decoupling control approach based on inverse system has been used for the innovative five degree-of-freedom bearingless induction motor, which is multi-variable, nonlinear and high coupling.
针对新型五自由度无轴承异步电动机这一多变量、非线性、强耦合的系统，采用逆系统的方法进行解耦控制。
The paper presents extended inverse method for the linearization and decoupling control of high_order nonlinear system.
提出适合于高阶非线性系统线性化解耦的广义逆系统。
A multiple models neural network decoupling controller is designed to control the multivariable nonlinear discrete time system.
针对多变量非线性离散时间系统设计多模型神经网络解耦控制器。
Fermentation process is a time-variable, nonlinear, uncertain and multivariable coupling system, and high performance decoupling control is a target to seek.
发酵过程是一个时变，非线性，不确定性和多变量耦合系统，高性能解耦控制是一个寻求的目标。
A double-level neural network for feedforward decoupling control is proposed for the fermentation process characterized with time-variable, nonlinear, uncertain and multivariable coupling.
双级神经网络的前馈解耦控制提出了具有时变，非线性，不确定性和多变量耦合发酵过程中。
A comparative study of two decoupling control methods based on vector control and nonlinear multi-input-multi-output state-feedback based on theory of differential geometry is researched.
对异步电动机的矢量控制和基于微分几何理论的非线性多输入多输出状态反馈两种解耦控制方案作理论和试验比较研究。
Based on the class of nonlinear multi-variable system with the nonlinear operator and couple appearing in the input of system, the online decoupling control with NN is studied in this thesis.
本文主要针对非线性算子及耦合均在输入端的一类非线性多变量系统，研究如何采用神经网络实现其在线解耦控制。
At first, the fuzzy adaptive control scheme was designed to achieve the decoupling control of MIMO nonlinear system.
首先，设计基于精确反馈线性化的模糊解耦控制环节。
Appling decoupling algorithm to asymptotic output tracking of nonlinear singular control systems.
研究非线性奇异系统的解耦算法在渐近输出跟踪中的应用。
Discusses the nonelinearity and coupling of the plastics thickness control system, and adopts NN serial decoupling algorithm to solve the difficulty in multivariable nonlinear coupling.
讨论了薄膜厚度控制的非线性和耦合性，应用神经网络串行解耦算法，解决多变量非线性耦合问题，同时还采用了改进的学习算法———动量法，并与传统算法做了仿真比较。
Discusses the nonelinearity and coupling of the plastics thickness control system, and adopts NN serial decoupling algorithm to solve the difficulty in multivariable nonlinear coupling.
讨论了薄膜厚度控制的非线性和耦合性，应用神经网络串行解耦算法，解决多变量非线性耦合问题，同时还采用了改进的学习算法———动量法，并与传统算法做了仿真比较。
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