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Structural Decomposition and Decentralized Control of Petri Nets

Authors :
Zhiwu Li
MengChu Zhou
Jianhong Ye
Abdulrahman Al-Ahmari
Source :
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 48:1360-1369
Publication Year :
2018
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2018.

Abstract

Control of a large-scale automated manufacturing system is an important and challenging issue. Its discrete event system model represented by Petri nets tends to become highly complicated in structure, especially when there exist uncontrollable or unobservable events. The existing approaches are nontrivial to design both efficient and maximally permissive supervisors to impose constraints on an overall system. In this paper, instead of considering the control problem from an overall system perspective, we intend to transform an overall control problem into the one designing multiple controllers in parallel, each of which is much simpler in structure. A Petri net structure is decomposed via integer linear programming or a polynomial decomposition method to obtain multiple state-machine subnets that constitute a decentralized system. A necessary and sufficient condition for preserving the equivalence in terms of states and behaviors between the overall system and its decentralized version is reported. Constraints representing control requirements are further converted and enforced in the respective subnets. Then, supervisors are generated via a generalized mutual exclusion constraint method. By considering the deviations between the subnet control and overall control, this paper formulates a communication mechanism to guarantee that the decentralized system runs in an appropriate manner. Finally, two examples are presented to demonstrate the proposed approach.

Details

ISSN :
21682232 and 21682216
Volume :
48
Database :
OpenAIRE
Journal :
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Accession number :
edsair.doi...........33d9ae8123324e5259552806aa93aa34
Full Text :
https://doi.org/10.1109/tsmc.2017.2703950