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PSI: An Established Block-Oriented Simulation Program
Published in Derek A. Linkens, CAD for Control Systems, 2020
As soon as an operator becomes part of a simulation model, for example, in command and control systems, discrete events can be profitably utilized to model the human reaction. Also production systems, such as conveyor belts in assembly lines, can be described as discrete-event models. Discrete-event dynamic systems (DEDS) have become increasingly important for modeling event-driven, asynchronous dynamic systems [3]. Processes in discrete-event models can start at time t, other processes Te sec in the future. Then, at t+Te, the simulation will execute the intended action or process. Also for modeling timing sequences such as “after a trigger the switch should be closed for at least tmin sec and for a maximum time of tmax sec.” This model can be solved easily, accurately, and efficiently with the aid of two discrete-event processes: one process that takes care of an event tmin sec after a trigger and another process that realizes an event tmax sec after a trigger. There are only a very few simulation programs, among which are ACSL, PSI, and PHI, that support models with both differential equations and discrete events.
Introduction to the DEVS Modeling and Simulation Formalism
Published in Gabriel A. Wainer, Discrete-Event Modeling and Simulation, 2017
DEVS was created for modeling and simulating discrete-event dynamic systems (DEDS); thus, it defines a way to specify systems whose states change either upon the reception of an input event or due to the expiration of a time delay. In order to attack the complexity of the system under study, the model is organized hierarchically (i.e., it is organized in a way such that every element is higher than its precedent), and higher-level components of the system are decomposed into simpler elements. The second tool used to attack complexity is information hiding, through the provision of a modular interface for each of the models.
Colored Petri nets-based control and experimental validation on three-tank system level control
Published in International Journal of General Systems, 2023
Marius Brezovan, Radu-Emil Precup, Dan Selişteanu, Liana Stănescu
Apart from continuous- and discrete-time systems, a separate category of dynamical systems is discrete event dynamic systems (DEDS), referred to also as discrete event systems (DES), which are discrete and event-based systems, and their evolution depends on state transition tables, instead of differential equations. The control theory of DEDS is known as supervisory control theory (Ramadge and Wonham 1989), which is an active area of research especially in manufacturing. Recent approaches use Petri nets, usually low-level Petri nets or specific extensions of Petri nets, instead of finite state machines for implementing supervisors (Krogh 1987; Giua 2013). In the field of manufacturing systems, several approaches for using low-level Petri nets and high-level Petri nets for modeling both the manufacturing system and its controller have been proposed (Meng Chu Zhou, Dicesare, and Rudolph 1992; M. Zhou and Zhuang 1992; Feldmann et al. 1999).
Buffer allocation design for unreliable production lines using genetic algorithm and finite perturbation analysis
Published in International Journal of Production Research, 2022
Khelil Kassoul, Naoufel Cheikhrouhou, Nicolas Zufferey
Discrete-event dynamic systems (DEDS), such as manufacturing systems, are dynamic asynchronous system where the state transitions are initiated by the occurrence of discrete events in the system at instants of time. The evolution in time of a DEDS is analyzed using its trajectory, denoted by Nominal Trajectory (NT), representing the events that affect the entities processed by the system. Assuming that a parameter of the system is perturbed in a trajectory following the occurrence of an event, the value of the parameter changes, and a new trajectory is obtained, denoted by Perturbed Trajectory (PT).
On the static output feedback stabilisation of discrete event dynamic systems based upon the approach of semi-tensor product of matrices
Published in International Journal of Systems Science, 2019
Zhipeng Zhang, Zengqiang Chen, Xiaoguang Han, Zhongxin Liu
Discrete event dynamic system (DEDS) is one of the rapidly developing areas in system and control theory in the last decades (Ramadge & Wonham, 1987), and such systems can be found in many large and complex systems, man-made systems, such as flexible manufacturing systems, communication systems, transportation systems (Cassandras, 2015) and so on. Previous studies on the DEDSs have focused on the following aspects; In Brave and Heymann (1990), the stabilisation problem of the DEDSs modelled by deterministic finite automata with uncontrollable events was investigated and an algorithm to calculate the weak attraction region was proposed. In Takai, Ushio, and Kodama (1995), the static state feedback control of DEDSs under partial observation modelled by finite automata was investigated, and a necessary and sufficient condition was presented based on a mask which is a mapping from the state space to the observation space; In Queiroz, Cury, and Wonham (2005), the problem of multiple tasks in the supervisory control of DEDSs modelled by the coloured marking generator was investigated and the results allowed the synthesis of minimally restrictive supervisors; In Feng and Wonham (2008), the optimal non-blocking supervisors for DEDSs was investigated by introducing a flexible decentralised and hierarchical architecture, and the result guaranteed that coordinators and modular supervisors resulted in maximally permissive and non-blocking control; In Ushio and Takai (2016) and Yin (2017), the non-blocking supervisory control and supervisor synthesis problems of DEDSs modelled by Mealy automata with non-deterministic output functions was investigated; and some other problems were also reported such as concurrent supervisory control problem (Su, 2015) and supervisory control problem of DEDSs with state-dependent controllability (Wang & Cai, 2009).