Network architecture and communication modules for guaranteeing acceptable control and communication performance for networked multi-agent systems

Abstract

When sensory and actuation devices in a control system are exchanging data through one common communication medium, the sharing of communication bandwidth will induce unavoidable data latency and might degrade the control performance. Hence, the utilization of communication resource and the requirement of control specification should be analyzed and properly designed when implementing a control system over a network architecture. In this paper, we analyze the performance of information sharing of multiple cooperative agents over one communication network, and propose design methodologies of guaranteeing acceptable control and communication performance in a networked control system. In particular, we study the relationship between the sampling rates of a control system, and the transmission rates of a communication network, and then utilize an integrated networked control design chart to help select design parameters and visualize overall system performance at different sampling and transmission rates. Based on the design parameters selected, the communication modules by utilizing deadband control and state estimation are presented for guaranteeing both control and communication performance. Simulation studies are conducted in a network-and-control simulation tool that is developed on the Matlab/Simulink platform and is used to demonstrate the proposed design methodologies. Both the analysis and simulation results illustrate the characteristics of designing mechanisms between control and communication performance and show the improvement of implementing the proposed communication modules.

The Impact of Rate Adaptation Algorithms on Wi-Fi-Based Factory Automation Systems

“…The second one is related to the communication times necessary for transmitting data to the components distributed over the plant. Thus, for example, the instance of a control task in a networked system comprises, not only the time necessary to execute the control algorithm on a local controller, but also both the time necessary to acquire the feedback data, obtained from a message sent by remote sensors connected to the network, and the time to send control commands to remote actuators, again via the network [4]. Communication times play a critical role in task scheduling, since their values can be substantially higher than those due to local elaboration and, more importantly, they may be strongly variable.…”