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Data based models: an automatic method for model structure determination

机译:基于数据的模型:确定模型结构的自动方法

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A technique for automatically determining the structure of linear discrete-time models from real data is briefly illustrated. For pole-placement control system design, as shown in an example, it is essential that near, or exact, pole-zero cancellations should not occur within the model. It has been found that the Young's information criterion (YIC) statistic has consistently identified model structures that are free from such cancellations, and that subsequently result in good control system performance. Naturally, some control system design algorithms, for example predictive controllers, are insensitive to overparameterised models; however the YIC statistic is still useful, as it normally indicates the simplest model structure, which should result in minimum complexity controllers being designed.
机译:简要说明了一种根据实际数据自动确定线性离散时间模型的结构的技术。如示例所示,对于极点放置控制系统的设计,至关重要的是,模型内不应发生接近或精确的零极点抵消。已经发现,杨氏的信息标准(YIC)统计一直一致地确定了没有这种取消的模型结构,并且随后导致了良好的控制系统性能。自然地,某些控制系统设计算法,例如预测控制器,对过参数化的模型不敏感。但是,YIC统计信息仍然有用,因为它通常表示最简单的模型结构,这应该导致设计最小复杂度的控制器。

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