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Disturbance Model Identification and Model Free Synthesis of Controllers for Multivariable Systems

机译:多变量系统控制器的扰动模型辨识与模型免费综合

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摘要

In this work, two different problems are addressed. In the first part, the problem of synthesizing a set of stabilizing controllers for unknown multivariable systems using direct data is analyzed. This is a model free approach to control design and uses only the frequency domain data of the system. It is a perfect complement to modern and post modern methods that begin the control design with a system model. A three step method, involving sequential design, search for stability boundaries and stability check is proposed. It is shown through examples that a complete set of stabilizing controllers of the chosen form can be obtained for the class of linear stable multivariable systems. The complexity of the proposed method is invariant with respect to the order of the system and increases with the increase in the number of input channels of the given multivariable system. The second part of the work deals with the problem of identification of model uncertainties and the effect of unwanted exogenous inputs acting on a discrete time multivariable system using its output information. A disturbance model is introduced which accounts for the system model uncertainties and the effect of unwanted exogenous inputs acting on the system. The frequency content of the exogenous signals is assumed to be known. A linear dynamical model of the disturbance is assumed with an input that has the same frequency content as that of the exogenous input signal. The extended model of the system is then subjected to Kalman filtering and the disturbance states estimates are used to obtain a least squares estimate of the disturbance model parameters. The proposed approach is applied to a linear multivariable system perturbed by an exogenous signal of known frequency content and the results obtained depict the efficacy of the proposed approach.
机译:在这项工作中,解决了两个不同的问题。在第一部分中,分析了使用直接数据为未知多变量系统合成一组稳定控制器的问题。这是一种无模型的控制设计方法,仅使用系统的频域数据。它是对现代和后现代方法的完美补充,后者以系统模型开始控制设计。提出了一种三步法,包括顺序设计,寻找稳定性边界和稳定性检查。通过示例显示,对于一类线性稳定多变量系统,可以获取一组完整的所选形式的稳定控制器。所提出的方法的复杂度相对于系统顺序是不变的,并且随着给定多变量系统的输入通道数量的增加而增加。工作的第二部分涉及使用模型的输出信息识别模型不确定性以及不期望的外来输入对离散时间多变量系统的影响。引入了一种干扰模型,该模型考虑了系统模型的不确定性以及有害的外来输入对系统的影响。假定外源信号的频率含量是已知的。假设干扰的线性动力学模型的输入具有与外源输入信号相同的频率含量。然后,对系统的扩展模型进行卡尔曼滤波,并使用干扰状态估计来获得干扰模型参数的最小二乘估计。所提出的方法被应用于线性多变量系统,该系统受到已知频率含量的外来信号的干扰,所获得的结果描述了所提出的方法的有效性。

著录项

  • 作者

    Sajjanshetty Kiran;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 en_US
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