TARGETING USING GLOBAL-MODELS BUILT FROM NONSTATIONARY DATA

We show how to perform targeting control using global models derived f rom data coming from possibly nonstationary dynamical systems where th e varying parameters are known along with the System observations. We first identify a global model from the observations and the values of the accessible parameters. To carry out the control, we successively a pply the usual targeting algorithm to the model system to get a pertur bation of the accessible parameters for a given starting point and tar geting point, then apply this perturbation to the true system to gener ate a new starting point. Because our model is approximate, we repeat the targeting and perturbation steps until the observed trajectory is near the target point. (C) 1997 Elsevier Science B.V.