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|Title:||Supervisor simplification for AMS based on petri nets and inequality analysis||Authors:||Hu, Hesuan
|Keywords:||DRNTU::Engineering::Computer science and engineering||Issue Date:||2014||Source:||Hu, H., & Liu, Y. (2014). Supervisor simplification for ams based on petri nets and inequality analysis. IEEE Transactions on Automation Science and Engineering, 11(1), 66-77.||Series/Report no.:||IEEE transactions on automation science and engineering||Abstract:||In the framework of automated manufacturing systems (AMS), Petri nets are widely used to model, analyze, and control them. Resolving deadlocks is of paramount significance because their emergence may likely zero a systems throughput, if not necessarily. Supervisory control technique is the most widely adopted method to resolve them. A control policy can be converted into satisfying a set of inequalities, each of which corresponds to a siphon in a Petri net structure. The number of siphons can be exponential in the worst case, so does the number of inequalities. Taking into account the independent and dependent inequalities, this paper proposes a method to remove all the dependent inequalities, while preserving only the independent ones. This method can significantly reduce the size of a supervisory controller. Examples are presented to illustrate the effectiveness and efficiency of this method.||URI:||https://hdl.handle.net/10356/102332
|DOI:||http://dx.doi.org/10.1109/TASE.2013.2288645||Rights:||© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Published version of this article is available at [DOI: http://dx.doi.org/10.1109/TASE.2013.2288645]||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Journal Articles|
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