Stable model predictive control for constrained max-plus-linear systems

Reference:
I. Necoara, B. De Schutter, T.J.J. van den Boom, and H. Hellendoorn, "Stable model predictive control for constrained max-plus-linear systems," Discrete Event Dynamic Systems: Theory and Applications, vol. 17, no. 3, pp. 329-354, Sept. 2007.

Abstract:
Discrete-event systems with synchronization but no concurrency can be described by models that are "linear" in the max-plus algebra, and they are called max-plus-linear (MPL) systems. Examples of MPL systems often arise in the context of manufacturing systems, telecommunication networks, railway networks, parallel computing, etc. In this paper we provide a solution to a finite-horizon model predictive control (MPC) problem for MPL systems where it is required that the closed-loop input and state sequence satisfy a given set of linear inequality constraints. Although the controlled system is nonlinear, by employing results from max-plus theory, we give sufficient conditions such that the optimization problem that is performed at each step is a linear program and such that the MPC controller guarantees a priori stability and satisfaction of the constraints. We also show how one can use the results in this paper to compute a time-optimal controller for linearly constrained MPL systems.