• Researching on the non-linear PID controller.

    非线性PID悬浮控制方法研究。

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  • Designing the structure of betterment PID controller.

    设计改进型PID控制器结构。

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  • Next, the servo system's PID controller was designed.

    设计了电液伺服系统数字pid控制器。

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  • It proposes a simple and effective PID controller for integrating processes.

    针对积分过程,提出了一种简单、实用的PID控制器。

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  • And evaluate the performance of PID controller by the step response of the system.

    并通过系统响应曲线图对设计的PID控制器的性能进行评估。

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  • The improvement project for a compound fuzzy intellectual PID controller is presented.

    提出了一种复合型模糊智能PID控制器的改进方案。

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  • An optimal cascade PID controller based on restrictions of stable region was researched.

    提出一种稳定域约束的串级PID控制器的参数优化方法。

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  • It perfects the properties of PID controller and improves the precision of control system.

    进一步完善了PID控制器的性能,提高了系统的控制精度。

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  • A method is proposed for parameters tuning of normalized PID controller with chaos variables.

    提出了一种基于混沌优化的PID控制器参数整定方法。

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  • The test results show that the Repetitive Controller is better than the Enhanced PID Controller.

    实测结果表明重复控制技术在对周期性重复运动的控制上确实优于PID控制技术。

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  • A normal PID controller is used in industry, due to its simple structure and being realized easily.

    常规的PID控制器由于结构简单、实现容易,在工业控制中被广泛应用。

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  • The controller achieves the adaptation of normal PID controller parameters on line by fuzzy inferences.

    该控制器通过模糊推理实现PID控制器参数的在线调整。

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  • A new tuning method for PID controller design is proposed as a class of stable and minimum phase plants.

    该文为一类稳定的最小相位控制对象提出一种新的PID控制器的参数整定方法。

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  • The performance of PID controller lies in the choice of proportional, integral and different coefficient.

    PID控制器性能好坏的关键在于比例、积分和微分参数的选择。

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  • The parameters of the neural network PID controller are modified on line by the improved conjugate gradient.

    并用这种改进的共轭梯度法对神经网络PID控制器参数实现在线修正。

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  • The stable range of singularly perturbed maglev system parameter was studied based on cascade PID controller.

    研究采用串级PID控制的奇异摄动磁悬浮系统参数稳定范围。

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  • Neural network intelligence PID controller has many advanced properties compared with traditional PID controller.

    同传统的PID控制相比较,神经网络智能PID控制有许多优点。

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  • We can design a new kind of controller which has the advantage of both minimum tempo controller and PID controller.

    我们可以设计一种新的控制器同时具有两者的优点。

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  • Auto disturbance rejection controller (ADRC) is put forward based on PID controller in order to overcome its own defects.

    为了克服PID控制器自身具有的缺陷,在PID的基础上提出了自抗扰控制器(adrc)。

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  • The success in debugging the fuzzy PID controller can provide favorable reference in interrelated research and experiment.

    模糊pid控制器调试的成功,可作为拓展其他相关研究和实验的有利参考。

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  • The controller contains two parts, one is a conventional PID controller and another is an on-line fuzzy inference mechanism.

    该控制器由两部分组成,一部分是常规PID控制器,另一部分是在线模糊推理机构。

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  • For the voltage controlled system model, pole point method is taken to design the PID controller, and good result is achieved.

    对于电压控制对象模型,采用极点配置的方法设计PID控制器,均取得了较为满意的控制效果。

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  • In the direct numerical control system of the computer, PID controller is realized by the PID controlling algorithm procedure.

    在计算机直接数字控制系统中,PID控制器是通过计算机PID控制算法程序实现的。

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  • The stable design rules of the fuzzy PID controller were obtained based on its relationship with the traditional PID controller.

    最后利用模糊PID控制器与传统PID控制器的联系,进一步推算出符合稳定性要求的模糊PID控制器设计规则。

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  • For the stochastic system with white noise input, the consistency problem of desired indices for PID controller is investigated.

    针对具有随机白噪声输入的随机系统,分析了PID控制下期望指标的相容性问题。

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  • Based on the experiment, the mathematical model of close-loop temperature-controlling system and PID controller were constructed.

    以实验为基础,建立了闭环温度控制系统的数学模型,构造了相应的PID控制器。

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  • PID controller is widely used in the industry control process, but the parameters tuning is still a problem that people concerned.

    PID控制器在当前的工业过程控制中仍有着广泛的应用,但其控制参数整定一直是难点问题之一。

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  • The results show that the controller is better in comparison with traditional PID controller, especially under strong disturbance.

    结果表明,滑模模糊控制的性能明显优于PID控制,在强干扰时表现出良好的鲁棒性。

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  • The control system model consists of control strategy, sensors and actuators sub models. The control strategy is a PID controller.

    控制系统模型包括控制策略、传感器和执行器模型,本文选用的控制策略为PID调节器。

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  • With the use of the auto-tuning optimal PID controller, the optimal control over the air temperature in the greenhouse is realized.

    采用参数自整定最优PID控制算法,实现了温室温度的优化控制。

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