Real-Time Identification of Time-Varying ARMAX Systems Based on Recursive Update of Its Parameters

Abstract

A new method for identification of time-varying ARMAX systems is introduced. This method is based on expansion of time-varying parameters of the ARMAX model onto a set of basis functions. A recursive formulation for updating the coefficients of the basis functions of the time-varying parameters of the system is proposed. Similar to non-real-time basis-function methods, the proposed real-time method has the capability of tracking fast changes in the parameters of a time-varying system much better than the standard Kalman and recursive least-squares (RLS) methods. A computationally efficient version of the algorithm is also presented with a small degradation in tracking properties of the original algorithm. Selection of different types of basis functions makes the new method very flexible for different applications.