Second order theory of min-linear systems and its application to discrete event systems

Author(s):  
G. Cohen ◽  
S. Gaubert ◽  
R. Nikoukhah ◽  
J.P. Quadrat
1993 ◽  
Vol 26 (2) ◽  
pp. 679-682 ◽  
Author(s):  
G. Cohen ◽  
S. Gaubert ◽  
J.-P. Quadrat

2019 ◽  
Vol 30 (1) ◽  
pp. 25-54 ◽  
Author(s):  
Bart De Schutter ◽  
Ton van den Boom ◽  
Jia Xu ◽  
Samira S. Farahani

AbstractThe objective of this paper is to provide a concise introduction to the max-plus algebra and to max-plus linear discrete-event systems. We present the basic concepts of the max-plus algebra and explain how it can be used to model a specific class of discrete-event systems with synchronization but no concurrency. Such systems are called max-plus linear discrete-event systems because they can be described by a model that is “linear” in the max-plus algebra. We discuss some key properties of the max-plus algebra and indicate how these properties can be used to analyze the behavior of max-plus linear discrete-event systems. Next, some control approaches for max-plus linear discrete-event systems, including residuation-based control and model predictive control, are presented briefly. Finally, we discuss some extensions of the max-plus algebra and of max-plus linear systems.


2020 ◽  
Vol 3 (2) ◽  
pp. 133-147
Author(s):  
Lathifatul Aulia ◽  
Widowati Widowati ◽  
R. Heru Tjahjana ◽  
Sutrisno Sutrisno

Discrete event systems, also known as DES, are class of system that can be applied to systems having an event that occurred instantaneously and may change the state. It can also be said that a discrete event system occurs under certain conditions for a certain period because of the network that describes the process flow or sequence of events. Discrete event systems belong to class of nonlinear systems in classical algebra. Based on this situation, it is necessary to do some treatments, one of which is linearization process. In the other hand, a Max-Plus Linear system is known as a system that produces linear models. This system is a development of a discrete event system that contains synchronization when it is modeled in Max-Plus Algebra. This paper discusses the production system model in manufacturing industries where the model pays the attention into the process flow or sequence of events at each time step. In particular, Model Predictive Control (MPC) is a popular control design method used in many fields including manufacturing systems. MPC for Max-Plus-Linear Systems is used here as the approach that can be used to model the optimal input and output sequences of discrete event systems. The main advantage of MPC is its ability to provide certain constraints on the input and output control signals. While deciding the optimal control value, a cost criterion is minimized by determining the optimal time in the production system that modeled as a Max-Plus Linear (MPL) system. A numerical experiment is performed in the end of this paper for tracking control purposes of a production system. The results were good that is the controlled system showed a good performance.


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