ノンパラメトリック区分的アフィンモデルのℓ₁ 最適化に基づく単純化

抄録

This paper is concerned with construction of non-parametric PWA(Piecewise Affine) models using ℓ₁ optimization. Though its effectiveness was demonstrated in the literature, the number of modes in the models tends to increase over ten thousands. Hence it is difficult to apply the existing control methods. This paper proposes a method to reduce the modes of this model by defining the significance of data based on ℓ₁ optimization. Also by this method the size of data to represent this model becomes small. The performance of the method is shown through an application to the non-parametoric PWA model of motor.