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LPV System Local Model Interpolation Based on Combined Model Reduction

机译:LPV系统基于组合模型减少的本地模型插值

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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:Linear参数变化(LPV)系统标识的本地方法包括内插线性时间不变(LTI)模型,这些模型已经从非线性系统的不同工作点获取的数据估计。内插对这种方法至关重要。当局部LTI模型处于状态空间形式时,随着每个本地模型可以以任意状态估计,它被广泛地确认本地模型应在其插值之前连贯。为了避免使局部空间模型相干的微妙任务,本文提出了一种新的局部空间模型的新插值方法,这不需要连贯的本地模型。该方法基于通过组合本地模型构建的大状态空间模型的减少。提出了数值例子以说明该方法的有效性。

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