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A novel method of nonlinear system-simulation with uncertain parameters providing guaranteed bounds

机译:提供不确定范围的不确定参数非线性系统仿真的新方法

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Uncertain or unknown parameters are often an essential part in several biological or technical applications represented by nonlinear systems. These uncertainties cause numerical and analytical problems in finding guaranteed bounds for the solution of the state space representation for such systems. Unfortunately several industrial applications are demanding exactly these guaranteed bounds in order to fulfil regulations by the state authorities. A common and well known method to perform simulations with uncertain parameters is the Monte-Carlo method. This method with its stochastic approach cannot deliver guaranteed bounds. Methods using interval arithmetic provide a lot of overestimation. Thus we have to develop a novel method to find guaranteed bounds as an initial interval for further methods based on interval arithmetic. In this scope a new method is presented which is using a linear Lyapunov like functions to solve this problem. We achieve guaranteed and finite simulation bounds as a result of our approach. The idea is to find an auxiliary function, which helps to bind the state variables. An example from an industrial application completes the paper.
机译:不确定或未知参数通常是非线性系统代表的几种生物学或技术应用中的重要组成部分。这些不确定性在为此类系统的状态空间表示的求解找到保证界限时引起数值和分析问题。不幸的是,为了满足州政府的规定,一些工业应用正严格要求这些保证范围。蒙特卡罗方法是一种常见的,具有不确定参数的仿真方法。此方法及其随机方法无法提供保证的范围。使用区间算术的方法提供了很多高估。因此,我们必须开发一种新颖的方法来找到保证边界作为初始间隔,以用于基于间隔算术的其他方法。在此范围内,提出了一种新方法,该方法使用类似线性Lyapunov的函数来解决此问题。由于我们的方法,我们达到了有保证的有限仿真界限。这个想法是找到一个辅助函数,该函数有助于绑定状态变量。来自工业应用的示例完善了本文。

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