A Black-Box Identification Method for Automated Discrete-Event Systems

作者：Paula Estrada Vargas Ana; Lopez Mellado Ernesto; Lesage Jean Jacques

来源：IEEE Transactions on Automation Science and Engineering, 2017, 14(3): 1321-1336.

DOI：10.1109/TASE.2015.2445332

• Black-box identification
• discrete-event systems
• interpreted Petri nets

This paper deals with the identification of discrete-event manufacturing systems that are automated using a programmable logic controller (PLC). The behavior of the closed-loop system (PLC and Plant) is observed during its operation and is represented by a single long sequence of observed input/output (I/O) signals vectors. The proposed method follows a black-box and passive identification approach that allows addressing large and complex industrial DES and yields compact and expressive interpreted Petri net (IPN) models. It consists of two complementary stages; the first one obtains, from the I/O sequence, the reactive part of the model composed by observable places and transitions. The I/O sequence is also mapped into a sequence of the created transitions, from which the second stage builds the non observable part of the model including places that ensure the reproduction of the observed input output sequence. This method, based on polynomial-time algorithms on the size of the input data, has been implemented as a software tool that generates and draws the IPN model; it has been tested with input/output sequences obtained from real systems in operation. The tool is described and its application is illustrated through a case study.
Note to Practitioners-Automated modeling of controlled discrete manufacturing systems can be achieved by efficient identification algorithms that cope with large and complex plants performing concurrent and repetitive tasks a priori unknown. The black-box identification procedure processes an input/output sequence recorded during the system functioning for a long period of time, and then yields a comprehensive model of the closed-loop controlled system; this model approximates closely the actual behavior of the compound system controller-plant. A tool based on identification algorithms constitutes an excellent resource for computer-aided reverse engineering of controlled manufacturing systems. The method proposed herein allows processing sequences composed by thousands of I/O vectors in a few seconds.

• 出版日期2017-7