Graphical Modeling and Analysis Software for State Space-Based Optimization of Discrete Event Systems
Author(s) -
Jun Tang,
Feng Zhu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2852324
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In view of the particular research objectives rather than the system's characteristics, almost all systems can be discretized regardless of original continuous or discrete pattern. Modeling oriented to discrete-event system (DES) represents the dynamics of a system as a series of discrete events that perform changes in the state of the system, constituting the state space which supports the further analysis for scheduling and optimization. In this paper, the graphical modeling and analysis software (GMAS) as a platform for modeling DES is introduced with the basic notions and a general perspective on the systems approach. It clearly provides the graphic modeling and analysis interface. Besides, the system evolution process is recorded and represented by state space, transforming the optimization problem into a search-based issue in the reachability tree of finding the optimal or near-optimal sequence of function component activations from some initial state to the goal state. To validate its efficacy and practicability, a causal encounter model of traffic collision avoidance system operations is proposed in the GMAS formalism. The model has been proved to not only provide a better comprehension of the potential collision occurrences for risk assessment by representing the cause-effect relationship of each action but also aid the crews in the involved aircraft to make a cooperative and optimal option.
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