Orthogonal least square algorithm and its application for modelling suspension system

Abstract

A mathematical model is important to find a dynamic response of a system. The information obtained from the model could be used for investigation and analysis. Modelling based on input and output data is known as system identification. One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. Orthogonal least square estimation is an algorithm which can determine the structure of a model by identifying the significant terms contributed to the model and also capable of providing the final values of parameter estimates. The derivation of the algorithm is presented and its application to the modelling of a car suspension system is included to demonstrate the effectiveness of the algorithm.