自适应系统参数估计算法的综合

S. Lazarenko, I. Pugachev, A. Kostoglotov, Igor Deryabkin
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引用次数: 0

摘要

当前通过最小化观测值残差来确定自适应动态系统参数的问题。所提出的辨识方法可以通过构造不变量来获得关于状态变量和参数的新的反馈结构。它们允许通过使用根据变分法在真实轨迹上暴露的附加属性来形式化参数动力学中的先验不确定性,该变分法遵循Hamilton - Ostrogradskii原理,该原理是自适应系统和参数动力学的基础。变异特性允许将识别系统分解为参数和状态估计的子系统。它们之间的关系由灵敏度函数方程决定。非线性动态系统调节器参数辨识问题的求解结果验证了综合辨识算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The synthesis of algorithms for parameters estimation of adaptive systems
The problem of current determining the parameters of the adaptive dynamic systems by minimizing the residuals of observations. The developed identification method allows to obtain the new structures of feedbacks with respect to the state variables and the parameters by constructing invariants. They allow to formalize a priori uncertainty in the parameters dynamics through the use of additional properties that are exposed at the true trajectory in accordance with the variation method, which follows from the Hamilton — Ostrogradskii principle which is the base for the dynamics of the adaptive system and the parameters. The variations properties allow to decompose the identification system into the subsystems of the parameter and status estimation. The relationship between them is determined by the equation for the sensitivity function. The constructiveness of the synthesized algorithms of identification is confirmed by the results of solution the problem of identifying the parameters of the nonlinear dynamic system regulator.
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