PREDICTION CONTROL OF SDOF SYSTEM

General discussions are presented on an instantaneous optimal predicti on control, which includes a series of identification, prediction, and control on a single degree of freedom (SDOF) system. First, a method for the identification of the dynamic properties of the system, which is modeled by a multivariate autoregressive moving average (ARMA) mode l, is investigated with the responses of the system excited by an acti ve control device. Then general modes of an instantaneous optimal pred iction control rule are formulated in terms of the identified componen ts of the coefficient matrix of the ARMA model and the weights include d in the control objective function. The prediction control rule is in terpreted as an equivalent neural-network model whose links have physi cally meaningful weights.