Order Determination of Linear Systems Using Convolutional Neural Networks

Abstract

In this paper, a fast, intelligent model is proposed for the order determination of linear dynamical systems by using convolutional neural networks. This model estimates the dynamic order of the system with considerably lower excitation order of stimulation signal and without any prior knowledge in comparison to former works. To this end, only step response of the system is taken to estimate the dynamic order for both stable and unstable linear systems. Unlike the conventional methods, in this deep-based approach, the order determination is performed quickly, automatically, at a low cost, and without any iteration. In addition, it is demonstrated that the proposed approach has low sensitivity against delay and noise. Such an intelligent model can satisfy the demands for a fast identifier in online and plug-and-play controllers.