Adaptive model predictive control for max-plus-linear discrete event input-output systems

Reference:
T.J.J. van den Boom, B. De Schutter, G. Schullerus, and V. Krebs, "Adaptive model predictive control for max-plus-linear discrete event input-output systems," IEE Proceedings - Control Theory and Applications, vol. 151, no. 3, pp. 339-346, May 2004.

Abstract:
Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Recently, we have extended MPC to a class of discrete event systems that can be described by a model that is "linear" in the max-plus algebra. In our previous work we have considered MPC for the time-invariant case. In this paper we consider an adaptive scheme for the time-varying case, based on parameter estimation of input-output models. In a simulation example we show that the combined parameter-estimation/MPC algorithm gives a good closed-loop behavior.