Modeling of Non-uniformly Sampled Systems by Support Vector Regression with Applications

摘要

This paper presents a modeling method for a non-uniformly sampled system based on support vector regression (SVR).First,a lifted discrete-time state-space model for a non-uniformly sampled system is derived by using the lifting technique to reduce the modeling difficulty caused by multirate sampling.Then,the system is divided into several parallel subsystems and their input-output model is presented to satisfy the SVR model.Finally,an on-line SVR technique is utilized to establish the models of all subsystems to deal with uncertainty.Furthermore,the presented method is applied in a multichannel electrohydraulic force servo synchronous loading system to predict the system outputs over the control sample interval and the prediction mean absolute percentage error reaches 0.092%.The results demonstrate that the presented method has a high modeling precision and the subsystems have the same level of prediction error.