On Optimal Input Design for Model Predictive Control

Abstract — This paper considers a method for optimal input design in system identification for control. The approach addresses model predictive control (MPC). The objective of the framework is to provide the user with a model which guarantees that a specified control performance is achieved, with a given probability. We see that, even though the system is nonlinear, using linear theory in the input design can reduce the experimental effort. The method is illustrated in a minimum power input signal design in system identification of a water tank system. I