Closed Loop Predictive Optimal Control Algorithm Using ARMA Models

Abstract

A predictive optimal control algorithm based on auto-regressive moving average (ARMA) models has been developed. Being a closed loop algorithm, it can be used in the control of structures against any source of random excitation without any special arrangement for measuring the excitation. The algorithm combines two mathematical models: (1) An ARMA model representing the environment and the structure as a single system subjected to the unknown random excitation; and (2) a single-degree-of-freedom system, which represents the structure subjected to a known history of control force only. Unlike some ARMA based control algorithms, which are only for seismic excitations, the proposed algorithm permits the control system to be operational under any type of dynamic load. This results in a large reduction in the standby time of the control system and increases its reliability. In comparison with these algorithms, the proposed algorithm requires less measurements and sensors. The algorithm has the option for reducing or avoiding time delay.