• This paper gives a proportion controller combined by fuzzy control and expert control.

    提出了一种模糊控制与专家控制相结合的比例控制器。

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  • The coordinate changing method used to bring the CAM theory profile of the eccentricity rotor tri-proportion controller was introduced in this paper.

    本文介绍一种通过坐标变换生成容积式偏心转子比例控制器凸轮理论廓线的方法。

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  • The paper bring forward a fuzzy controller of self-tuning proportion factor based on PI arithmetic.

    本文提出一种基于PI算法的自调整比例因子模糊控制器。

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  • The inverter system adopts digital fuzzy controller with feed forward correction and which proportion coefficient and integral coefficient is changeable, so dynamic response is improved.

    逆变系统采用带前馈校正的变比例变积分系数的模糊控制器,提高了系统的动态响应指标;

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  • The inner loop USES a general proportion adjuster and the outer loop USES a single neuron PID controller with identification implement.

    内回路采用常规比例调节器,外回路采用带辨识器的单神经元pid控制器。

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  • Simulation results show that the dynamic characteristic of electro-hydraulic proportion controlling radial piston pump using this self-adapting fuzzy PID controller is very good.

    仿真结果表明,基于自适应模糊PID控制器的电液比例排量变量泵具有良好的动态性能。

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  • The fuzzy controller of self-adjusting proportion factor is a fuzzy controller that USES a certain way to adjust its proportion factor automatically, and gets the control aim hoped.

    自调整比例因子模糊控制器是利用一定的方式自动调整模糊控制器的比例因子,从而达到期望的控制目的。

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  • A systematical method of fuzzy controller design is introduced based on the Popov stability criterion and proportion property of input to output of the fuzzy controller.

    利用模糊控制器具有的输入输出比例特性及非线性系统的波波夫稳定判据,提出了在保证被控系统稳定的前提下模糊控制器的系统化设计方法。

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  • The proper fuzzy rules and proportion quantification factors were chosen in fuzzy controller. In addition, proportional and integral factors were selected in PI regulator.

    对模糊控制器选择了适当的模糊规则和合适的比例量化因子,并且对PI比例调节器选择了合适的比例积分因子。

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  • Which is based on the proposed RBF neural network inverse controller and a proportion differential controller.

    并提出一种基于RBF神经网络逆控制与比例微分控制相结合的双模控制策略。

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  • Which is based on the proposed RBF neural network inverse controller and a proportion differential controller.

    并提出一种基于RBF神经网络逆控制与比例微分控制相结合的双模控制策略。

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