Estimating delays in networked control systems using colored Petri nets and Markov chain models

This paper presents a novel two-step approach for modeling forward and backward network delays in networked control systems (NCS). The first step is to build a colored Petri net (CPN) structural model for the simulation of Ethernet based networked control systems. The modular model captures the most important features of industrial networked control systems, such as client/server input/output scanning and cyclical execution of the control algorithm on a programmable logic controller (PLC). CPN tools software is used to build and simulate the model with different parameter sets. This first easy to build model is used in a second step to identify a compact phenomenological model from an extensive set of simulation results. In this second step a finite state Markov chain delay model (FSMD) is used to capture the delay patterns generated with the CPN model. The resulting model is more compact than the CPN model and due to its mathematical form it can be integrated in existing design and analysis methods for NCS.