A New Approach for ARMA Pole Estimation Using Higher-Order Crossings
For control engineers, this provides a memory-efficient way to estimate poles for performance monitoring, but the method is incremental.
The paper introduces a method for estimating ARMA model poles using higher-order crossings, which requires only crossing counts to be stored. The approach is applied to control loop performance evaluation.
The paper describes a new method for estimating the poles of an ARMA model using higher-order crossings. The method involves transforming counts of crossing events into estimates of ARMA poles via the autocorrelation domain. An important advantage of the method is that the crossing counts are the only features that need to be stored from the original data. The poles of an ARMA model of a control loop correspond to the roots of the characteristic equation and are thus useful for evaluating control performance.