论文标题
具有降低保守性的非线性模型的线性参数变化嵌入
Linear Parameter-Varying Embedding of Nonlinear Models with Reduced Conservativeness
论文作者
论文摘要
在本文中，开发了一种系统的方法，将非线性系统的动态描述嵌入到线性参数变化（LPV）系统表示中。最初，使用多元多项式回归近似模型表示中的非线性函数。考虑到近似值作为潜在的调度参数的残差，进行了原理分析（PCA），以在应对Trade-O时引入有限的辅助调度参数？在模型准确性和复杂性之间。通过这种方式，共同执行非线性系统和调度变量选择的LPV嵌入，以使得良好的交易？可以找到复杂性和保守性之间。开发的LPV模型在多项式上取决于某些状态变量，并亲切地取决于引入的辅助调度变量，这些变量均包含整体调度向量。该方法还应用于两度自由（二-DOF）机器人操纵器外，除了一个学术示例外，还可以揭示所提出的方法的有效性，并与文献中一些可用的结果相比，展示了提出的方法的优点。
In this paper, a systematic approach is developed to embed the dynamical description of a nonlinear system into a linear parameter-varying (LPV) system representation. Initially, the nonlinear functions in the model representation are approximated using multivariate polynomial regression. Taking into account the residuals of the approximation as the potential scheduling parameters, a principle component analysis (PCA) is conducted to introduce a limited set of auxiliary scheduling parameters in coping with the trade-o? between model accuracy and complexity. In this way, LPV embedding of the nonlinear systems and scheduling variable selection are jointly performed such that a good trade-o? between complexity and conservativeness can be found. The developed LPV model depends polynomially on some of the state variables and affinely on the introduced auxiliary scheduling variables, which all together comprise the overall scheduling vector. The methodology is applied to a two-degree of freedom (2-DOf) robotic manipulator in addition to an academic example to reveal the effectiveness of the proposed method and to show the merits of the presented approach compared with some available results in the literature.
