Abstract

The nature of wireless propagation may reduce the QoS of the applications, such that some packages can be delayed or lost. For this reason, the design of wireless control applications must be faced in a holistic way to avoid degrading the performance of the control algorithms. This paper is aimed at improving the reliability of wireless control applications in the event of communication degradation or temporary loss at the wireless links. Two controller levels are used: sophisticated algorithms providing better performance are executed in a central node, whereas local independent controllers, implemented as back-up controllers, are executed next to the process in case of QoS degradation. This work presents a reliable strategy for switching between central and local controllers avoiding that plants may become uncontrolled. For validation purposes, the presented approach was used to control a planar robot. A Fuzzy Logic control algorithm was implemented as a main controller at a high performance computing platform. A back-up controller was implemented on an edge device. This approach avoids the robot becoming uncontrolled in case of communication failure. Although a planar robot was chosen in this work, the presented approach may be extended to other processes. XBee 900 MHz communication technology was selected for control tasks, leaving the 2.4 GHz band for integration with cloud services. Several experiments are presented to analyze the behavior of the control application under different circumstances. The results proved that our approach allows the use of wireless communications, even in critical control applications.

Highlights

  • Modern Industry 4.0 applications improve the productivity, efficiency, safety and intelligence of the production processes

  • Wireless control systems must be designed in a holistic way considering both the communications Quality of Service (QoS) and the control algorithm since they are intertwined [19,20,21]

  • The total number of lost frames in the test was of 45 frames which accounts for the 5% of total frames

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Summary

Introduction

Modern Industry 4.0 applications improve the productivity, efficiency, safety and intelligence of the production processes. They involve different operations such as monitoring, predictive maintenance, supervision and control operations [1,2]. In this scenario, Cyber Physical Production Systems (CPS/CPPS) [3] play a key role. Since they must connect the cyber platforms with the physical world providing adequate Quality of Service (QoS) parameters. Industrial applications require bounding certain QoS parameters, in particular delay, jitter and error rate

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