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Evolutionary Tuning Method for PID Controller Parameters of a Cruise Control System Using Metamodeling

机译:基于元模型的巡航控制系统PID控制器参数进化整定方法

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摘要

For long time the optimization of controller parameters uses the well-known classical method such as the Ziegler-Nichols and the Cohen-Coon tuning techniques. Despite its effectiveness, these off-line tuning techniques can be time consuming especially for a case of complex nonlinear system. This paper attempts to show a great deal on how Metamodeling techniques can be utilized to tune the PID controller parameters quickly. Note that the plant use in this study is the cruise control system with 2 different models, which are the linear model and the nonlinear model. The difference between both models is that the disturbances were taken into consideration for the nonlinear model, but in the linear model the disturbances were assumed as zero. The Radial Basis Function Neural Network Metamodel is able to prove that it can minimize the time in tuning process as it is able to give a good approximation to the optimum controller parameters in both models of this system.
机译:长期以来,控制器参数的优化使用了著名的经典方法,例如Ziegler-Nichols和Cohen-Coon调整技术。尽管具有离线效果,但这些离线调整技术仍然非常耗时,特别是对于复杂的非线性系统而言。本文试图就如何利用元建模技术来快速调节PID控制器参数进行大量展示。注意,在这项研究中,工厂使用的巡航控制系统具有两种不同的模型,分别是线性模型和非线性模型。两种模型之间的差异在于,非线性模型考虑了干扰,而线性模型中的干扰被假定为零。径向基函数神经网络元模型能够证明它可以最小化调整过程中的时间,因为它可以很好地近似该系统两个模型中的最佳控制器参数。

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  • 来源
    《Modelling and simulation in engineering》 |2009年第2009期|P.9.1-9.8|共8页
  • 作者单位

    Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Johor Darul Takzim, 81310 Skudai, Malaysia;

    Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Johor Darul Takzim, 81310 Skudai, Malaysia;

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