Distinguishability Analysis for Multiple Mass Models of Servo Systems with Commissioning Sensors

M. Tantau, Lars Perner, M. Wielitzka
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引用次数: 0

Abstract

Physically motivated models of electromechanical motion systems enable model-based control theory and facilitate system interpretation. Unfortunately, the effort of modelling restricts the usage of model-based methods in many applications. Some approaches to automatically generate models from measurements choose the best model based on minimizing the residual. These model selection attempts are limited due to ambiguities in reconstructing the internal structure from the input-output behaviour because usually motion systems have only one actuator and one sensor. Often, it is unknown if the resulting model is unique or if other models with different structure would fit equally well. The set of candidate models should be designed to contain only distinguishable models but ambiguities are often unknown to the experimenter. In this paper distinguishability is investigated systematically for a class of multiple mass models representing servo positioning systems. In the analysis a new criterion for indistinguishability is used. The benefit of additional, structural sensors on distinguishability of models is demonstrated which suggests to mount them temporarily for the commissioning phase in order to facilitate the model selection. It turns out that the best results can be achieved if synergies among sensor signals are utilized.
带调试传感器伺服系统多质量模型的可分辨性分析
机电运动系统的物理激励模型使基于模型的控制理论和方便的系统解释。不幸的是,建模工作限制了基于模型的方法在许多应用中的使用。一些从测量数据中自动生成模型的方法基于残差最小化来选择最佳模型。由于运动系统通常只有一个执行器和一个传感器,因此从输入-输出行为重建内部结构时存在歧义,因此这些模型选择尝试受到限制。通常,我们不知道得到的模型是否是唯一的,或者其他具有不同结构的模型是否也能很好地拟合。候选模型集应该设计成只包含可区分的模型,但实验者通常不知道模糊性。本文系统地研究了代表伺服定位系统的一类多质量模型的可分辨性。在分析中使用了一种新的不可分辨性准则。额外的结构传感器对模型的可识别性的好处被证明,这建议在调试阶段临时安装它们,以便于模型选择。结果表明,利用传感器信号之间的协同效应可以达到最佳效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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