论文标题
基于确定的Narx多项式模型的非线性补偿
Nonlinearity Compensation Based on Identified NARX Polynomials Models
论文作者
论文摘要
本文使用具有外源输入（NARX）的非线性多项式自回归模型来处理动态系统中非线性的补偿。补偿方法是针对静态和动态环境及其对滞后系统的适应性制定的。在所有这些情况下，都使用已识别的NARX模型。核心思想是将模型重写为代数多项式，其根是潜在的补偿输入。提出一个程序，以选择最适当的根，在不止一个的情况下。给出了数值和实验结果以说明该方法。在实验情况下，该方法与其他方法进行了比较。结果表明，所提出的方法可以提供补偿输入信号，该信号实际上使用不超过五个术语的简单和代表性模型对研究系统进行线性性化。
This paper deals with the compensation of nonlinearities in dynamical systems using nonlinear polynomial autoregressive models with exogenous inputs (NARX). The compensation approach is formulated for static and dynamical contexts, as well as its adaptation to hysteretic systems. In all of these scenarios, identified NARX models are used. The core idea is to rewrite the model as an algebraic polynomial whose roots are potential compensation inputs. A procedure is put forward to choose the most adequate root, in cases where more than one is possible. Both numerical and experimental results are presented to illustrate the method. In the experimental case the method is compared to other approaches. The results show that the proposed methodology can provide compensation input signals that practically linearize the studied systems using simple and representative models with no more than five terms.
