This paper proposes an approach to find the eigenvalues and eigenvectors of a class of autonomous max-min-plus-scaling (MMPS) systems. First we show that time invariant, monotone and non-expansive MMPS systems with only time variables has a unique structural eigenvalue and eigenvector under some conditions. Then, we propose a mixed integer linear programming (MILP) algorithm to calculate the eigenvalue and the corresponding eigenvector for such systems. Finally, we present a modified linear programming (LP) algorithm to find all the eigenvalues of a general time invariant MMPS system.

We consider the growth rate of a switching max-min-plus-scaling (S-MMPS) system in a discrete-event framework. We show that an explicit, time-invariant, monotone, and arbitrarily switching MMPS system has a bounded growth rate. Further, we propose a mixed-integer linear programming problem to calculate the estimates of the smallest upper bound and the largest lower bound of the growth rate of an S-MMPS system.

In this paper, we discuss the stability of general time-invariant discrete-event systems modelled as max-min-plus-scaling (MMPS) systems. We analyze MMPS systems with two types of states: time states and quantity states. A set of linear programming problems are proposed to find the growth rates of the time states via a normalization of the MMPS system. Then a framework for stability analysis of the general time-invariant MMPS system is discussed with respect to the normalized system. The approach presented in this paper is an efficient way to study the stability of a general MMPS system.