Status monitoring in intelligent control system using a linear predictive coding algorithm

A reliable scheme based on a linear predictive coding algorithm (LPCA) is proposed for monitoring in real-time the status of the control system under both steady and transient states. An ARMA model of the error signal of the closed-loop control system is estimated using LPCA. In the transient state, using the ARMA coefficients, integral squared-error and pole-location-based unit step response measures and stability robustness using Kharitonov´s theorem are computed, and a fault is predicted. In the steady state, a deviation from the nominal model is detected from the ARMA-based power spectral estimates. The monitor displays information in decreasing order of importance and with increasing amounts of computation such that the essentials are known in the shortest possible time, with complete details emerging later. The proposed scheme is evaluated on a simulated complex multivariable control system