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LPV System Local Model Interpolation Based on Combined Model Reduction

机译：基于组合模型约简的LPV系统局部模型插值

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摘要

The local approach to linear parameter varying (LPV) system identification consists in interpolating a collection of linear time invariant (LTI) models, which have been estimated from data acquired at different working points of a nonlinear system. Interpolation is essential in this approach. When the local LTI models are in state-space form, as each local model can be estimated with an arbitrary state basis, it is widely acknowledged that the local models should be made coherent before their interpolation. In order to avoid the delicate task of making local state-space models coherent, a new interpolation method of local state-space models is proposed in this paper, which does not require coherent local models. This method is based on the reduction of the large state-space model built by combining the local models. Numerical examples are presented to illustrate the effectiveness of this method.
机译：线性参数变化（LPV）系统识别的本地方法包括对线性时不变（LTI）模型的集合进行插值，这些模型是根据在非线性系统的不同工作点获取的数据进行估算的。在这种方法中，插值至关重要。当局部LTI模型为状态空间形式时，由于可以以任意状态为基础来估计每个局部模型，因此众所周知，应该在插值之前使局部模型一致。为了避免使局部状态空间模型相干的繁琐任务，本文提出了一种不需要局部状态空间模型的新的局部状态空间模型插值方法。该方法基于通过合并局部模型而建立的大型状态空间模型的缩减。数值例子说明了该方法的有效性。

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