Modelling and Analysis of Complex System Dynamics Based on Orthogonal Matching Pursuit Algorithm

The problem of identifying non-linear system models is addressed by introducing the OMP（Orthogonal matching pursuit）algorithm for fast non-linear system modelling. The method aims to solve the problem of poor timeliness in modelling large data with NARX（Nonlinear autoregressive with exogenous inputs） models. Firstly, it is shown that the OLS（Orthogonal least squares）algorithm has the problem of many orthogonal times and time consuming, which can be effectively solved by using the OMP algorithm. The kinetic properties of the NARX model obtained by the OMP algorithm are verified using the model prediction method.Secondly, the effectiveness of the OMP algorithm system modelling is illustrated by taking a single degree of freedom non-linear system as an example. Finally, the NARX model of the cantilever beam is established using the OMP algorithm, and the NARX model prediction output is compared with the experimental measured output, the inherent frequency of the NARX model and the actual inherent frequency of th