Systems Modelling and Identification in CAN based Distributed Control Systems

Abstract Distributed control systems performance can be affected by the occurrence of jitter in the messages that carry relevant data such as sample and actuation variables. This jitter comes from the influence of messages from other sources and thus depends on factors such as the distribution of controller tasks and the medium access control used in the network. When a CAN- controller area network is considered, this jitter can be modelled as a random variable with a gamma distribution. In this paper a study of the influence of this specific type of jitter in system identification with recursive implementation is presented. The results are derived in an adverse situation when both sampling and actuation data suffer from jitter. It is shown that using a model that assumes fractional dead-time in the system leads to a much better parameter identification than when the problem is just ignored.