The Impact of Insurance on the Law of Torts

Abstract

An experimental study of "Model-on-Demand" (MoD) identification is made on a pilot-scale brine-water mixing tank. MoD estimation is compared against semi-physical modeling techniques using identification data generated from a systematically designed m-level Pseudo Random Sequence (PRS) input. The estimated models are the basis for evaluating the usefulness of MoD-based Model Predictive Control (MPC). For this application, MoD-MPC is shown to provide better performance at high bandwidths compared to a linear MPC controller