Chen-Fliess级数的输出可达性:牛顿-拉弗森方法

Ivan Perez Avellaneda, L. A. D. Espinosa
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引用次数: 2

摘要

Chen-Fliess级数的优化可以解决非线性仿射控制系统可达集的计算问题。这为可达性分析提供了一种输入-输出方法。牛顿-拉夫逊法是最重要的直线搜索数值算法之一。该方法基于感兴趣函数的Hessian近似和二阶Taylor近似的计算。目前,Chen-Fliess级数只有梯度下降等一阶优化方法。本文引入微分语言的框架,以便系统地描述Chen-Fliess级数的高阶导数。这是通过定义与Chen-Fliess级数的g teaux导数重合的单峰中的一个词的导数运算来实现的。在此背景下,给出了Chen-Fliess级数的Hessian、二阶Taylor近似和二阶优化条件。然后将Newton-Raphson算法应用于Chen-Fliess序列优化中,计算可达集。文中给出了实例和仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Output Reachability of Chen-Fliess series: A Newton-Raphson Approach
The optimization of Chen-Fliess series allows addressing the problem of the computation of reachable sets of nonlinear affine control systems. This provides an input-output approach to reachability analysis. The Newton-Raphson method is one of the most important line search numerical algorithms. The method is based on the computation of the Hessian and the second-order Taylor approximation of the function of interest. Currently, only first-order optimization methods, such as gradient descent, exist for Chen-Fliess series. In this paper, the framework of differential languages is introduced to allow a systematic description of higher-order derivatives of Chen-Fliess series. This is achieved by defining the derivative operation of a word in a monoid that coincides with the Gâteaux derivative of a Chen-Fliess series. In this context, the Hessian of a Chen-Fliess series, its second-order Taylor approximation, and the second-order optimization condition are provided for Chen-Fliess series. Then the Newton-Raphson algorithm is adapted to Chen-Fliess series optimization to compute reachable sets. Illustrative examples and simulations are presented throughout the paper.
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