Nonlinear system identification using extreme learning machine

Abstract

System identification is a very important part in control theory for nonlinear analysis and optimization. In the past years, neural identification of dynamic systems gains great interest because of its powerful mapping capability. In this paper, a learning algorithm for the feedforward neural network named extreme learning machine (ELM) is applied for nonlinear system identification problem. The simulation results show that ELM can achieve very satisfying identification performance and fast learning speed. © 2006 IEEE.