On Optimal Input Design for Model Predictive Control

This paper considers a method for optimal inputdesign in system identification for control. The approachaddresses model predictive control (MPC). The objective ofthe framework is to provide the user with a model whichguarantees that a specified control performance is achieved,with a given probability. We see that, even though the systemis nonlinear, using linear theory in the input design can reducethe experimental effort. The method is illustrated in a minimumpower input signal design in system identification of a watertank system.